Time Series Forecasting and Deep Learning

List of research papers focus on time series forecasting and deep learning, as well as other resources like competitions, datasets, courses, blogs, code, etc.

Table of Contents

• Scope
• Applications
• Benchmarks
• Papers
  • 2026
  • 2025
  • 2024
  • 2023
  • 2022
  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
• Blogs
• Competitions
• Courses
• Libraries
• Datasets
• Books
• Repositories
• Tutorials

Scope

This collection primarily focuses on time series forecasting. It also covers adjacent time series tasks, including anomaly detection, classification, imputation, generation, and representation learning.

Applications

• TimeGPT

  • Nixtla’s TimeGPT is a generative pre-trained forecasting model for time series data.

Benchmarks

• FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting

  • FinTSB is a comprehensive and practical financial time series benchmark.

• GIFT-Eval Time Series Forecasting Leaderboard

  • GIFT-Eval is a pioneering benchmark aimed at promoting evaluation across diverse datasets.

• It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks

  • TIME is a task-centric time series forecasting benchmark comprising various fresh datasets, tailored for zero-shot TSFM evaluation.

• QuitoBench — A High-Quality Open Time Series Forecasting Benchmark

  • QuitoBench is an evaluation benchmark with balanced coverage across eight trend×seasonality×forecastability (TSF) regimes—a difficulty-centric design that captures forecasting-relevant properties rather than application-defined domain labels.

Papers

Paper count: 640

2026

• Falcon-X: A Time Series Foundation Model for Heterogeneous Multivariate Modeling

  • 09 Jun 2026, Yiding Liu, et al.

  • [Official Code - Falcon-TST]

• Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting

  • 26 May 2026, Shuang Liang, et al.

  • [Official Code - TSCOMP]

• SeesawNet: Towards Non-stationary Time Series Forecasting with Balanced Modeling of Common and Specific Dependencies

  • 14 May 2026, Hao Li, et al.

  • [Official Code - SeesawNet]

• Characteristic Root Analysis and Regularization for Linear Time Series Forecasting

  • 13 May 2026, Zheng Wang, et al.

  • [Official Code - RootPurge]

• EventTSF: Event-Aware Non-Stationary Time Series Forecasting

  • 10 May 2026, Yunfeng Ge, et al.

  • [Official Code - EventTSF]

• TEDM: Time Series Forecasting with Elucidated Diffusion Models

  • 25 Apr 2026, Edgardo Solano Carrillo, et al.

  • [Official Code - TEDM]

• Re-Diffusion: Modeling Latent Residuals with Diffusion for Time-Series Forecasting

  • 12 Apr 2026, Boning Zhang, et al.

• AlphaCast: A Human Wisdom-LLM Intelligence Co-Reasoning Framework for Interactive Time Series Forecasting

  • 10 Apr 2026, Xiaohan Zhang, et al.

  • [Official Code - AlphaCast]

• TimeRecipe: A Time-Series Forecasting Recipe via Benchmarking Module Level Effectiveness

  • 25 Mar 2026, Zhiyuan Zhao, et al.

  • [Official Code - TimeRecipe]

• CoRA: Boosting Time Series Foundation Models for Multivariate Forecasting through Correlation-aware Adapter

  • 23 Mar 2026, Hanyin Cheng, et al.

  • [Official Code - CoRA]

• Time Tracker: Mixture-of-Experts-Enhanced Foundation Time Series Forecasting Model with Decoupled Training Pipelines

  • 18 Mar 2026, Aobo Liang, et al.

• TimeCAP: A Channel-Aware Pre-Training Framework for Multivariate Time Series Forecasting

  • 14 Mar 2026, Chuanru Ren, et al.

  • [Official Code - TimeCAP]

• From Tokenizer Bias to Backbone Capability: A Controlled Study of LLMs for Time Series Forecasting

  • 06 Mar 2026, Xinyu Zhang, et al.

• Position: Beyond Model-Centric Prediction -- Agentic Time Series Forecasting

  • 05 Mar 2026, Mingyue Cheng, et al.

• Adapt Data to Model: Adaptive Transformation Optimization for Domain-shared Time Series Foundation Models

  • 28 Feb 2026, Yunzhong Qiu, et al.

  • [Official Code - TATO]

• CPiRi: Channel Permutation-Invariant Relational Interaction for Multivariate Time Series Forecasting

  • 27 Feb 2026, Jiyuan Xu, et al.

  • [Official Code - CPiRi]

• Learning Recursive Multi-Scale Representations for Irregular Multivariate Time Series Forecasting

  • 25 Feb 2026, Boyuan Li, et al.

  • [Official Code - PyOmniTS]

• SciTS: Scientific Time Series Understanding and Generation with LLMs

  • 25 Feb 2026, Wen Wu, et al.

• TimeOmni-1: Incentivizing Complex Reasoning with Time Series in Large Language Models

  • 24 Feb 2026, Tong Guan, et al.

  • [Official Code - TimeOmni-1]

• SEMixer: Semantics Enhanced MLP-Mixer for Multiscale Mixing and Long-term Time Series Forecasting

  • 18 Feb 2026, Xu Zhang, et al.

  • [Official Code - SEMixer]

• MixLinear: Extreme Low Resource Multivariate Time Series Forecasting with 0.1K Parameters

  • 16 Feb 2026, Aitian Ma, et al.

  • [Official Code - MixLinear]

• Test-Time Efficient Pretrained Model Portfolios for Time Series Forecasting

  • 11 Feb 2026, Mert Kayaalp, et al.

• StretchTime: Adaptive Time Series Forecasting via Symplectic Attention

  • 09 Feb 2026, Yubin Kim, et al.

• Position: The Inevitable End of One-Architecture-Fits-All-Domains in Time Series Forecasting

  • 02 Feb 2026, Qinwei Ma, et al.

• Conformal Prediction Algorithms for Time Series Forecasting: Methods and Benchmarking

  • 30 Jan 2026, Andro Sabashvili, et al.

• A Comprehensive Survey of Deep Learning for Multivariate Time Series Forecasting: A Channel Strategy Perspective

  • 27 Jan 2026, Xiangfei Qiu, et al.

  • [Official Code - CS4TS]

• Beyond Accuracy: Are Time Series Foundation Models Well-Calibrated?

  • 26 Jan 2026, Coen Adler, et al.

• Time series forecasting with Hahn Kolmogorov-Arnold networks

  • 25 Jan 2026, Md Zahidul Hasan, et al.

  • [Official Code - HaKAN]

• ReCast: Reliability-aware Codebook Assisted Lightweight Time Series Forecasting

  • 09 Jan 2026, Xiang Ma, et al.

• TimeDistill: Efficient Long-Term Time Series Forecasting with MLP via Cross-Architecture Distillation

  • 07 Jan 2026, Juntong Ni, et al.

  • [Official Code - TimeDistill]

2025

• Dynamic Sector Fusion Transformer for Stock Index Prediction

  • 16 Dec 2025, Xu Wang, et al.

• FusAD: Time-Frequency Fusion with Adaptive Denoising for General Time Series Analysis

  • 16 Dec 2025, Da Zhang, et al.

  • [Official Code - FusAD]

• TwinFormer: A Dual-Level Transformer for Long-Sequence Time-Series Forecasting

  • 13 Dec 2025, Mahima Kumavat, et al.

  • [Official Code - TwinFormer]

• Sonnet: Spectral Operator Neural Network for Multivariable Time Series Forecasting

  • 09 Dec 2025, Yuxuan Shu, et al.

  • [Official Code - Sonnet]

• Time Series Forecasting via Direct Per-Step Probability Distribution Modeling

  • 28 Nov 2025, Linghao Kong, et al.

  • [Official Code - interPDN]

• RI-Loss: A Learnable Residual-Informed Loss for Time Series Forecasting

  • 27 Nov 2025, Jieting Wang, et al.

  • [Official Code - RI-Loss]

• SimDiff: Simpler Yet Better Diffusion Model for Time Series Point Forecasting

  • 24 Nov 2025, Hang Ding, et al.

• Adapformer: Adaptive Channel Management for Multivariate Time Series Forecasting

  • 18 Nov 2025, Yuchen Luo, et al.

• Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline

  • 17 Nov 2025, Xvyuan Liu, et al.

  • [Official Code - APN]

• OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting

  • 14 Nov 2025, Sisuo Lyu, et al.

  • [Official Code - OccamVTS]

• Beyond MSE: Ordinal Cross-Entropy for Probabilistic Time Series Forecasting

  • 13 Nov 2025, Jieting Wang, et al.

  • [Official Code - OCE-TS]

• MDMLP-EIA: Multi-domain Dynamic MLPs with Energy Invariant Attention for Time Series Forecasting

  • 13 Nov 2025, Hu Zhang, et al.

  • [Official Code - MDMLP-EIA]

• CaReTS: A Multi-Task Framework Unifying Classification and Regression for Time Series Forecasting

  • 12 Nov 2025, Fulong Yao, et al.

• EMAformer: Enhancing Transformer through Embedding Armor for Time Series Forecasting

  • 11 Nov 2025, Zhiwei Zhang, et al.

  • [Official Code - EMAformer]

• LEAF: Large Language Diffusion Model for Time Series Forecasting

  • 09 Nov 2025, Yuhang Pei, et al.

  • [Official Code - LEAF]

• This Time is Different: An Observability Perspective on Time Series Foundation Models

  • 04 Nov 2025, Ben Cohen, et al.

  • [Official Code - toto]

• SST: Multi-Scale Hybrid Mamba-Transformer Experts for Time Series Forecasting

  • 02 Nov 2025, Xiongxiao Xu, et al.

  • [Official Code - SST]

• Multi-Modal View Enhanced Large Vision Models for Long-Term Time Series Forecasting

  • 31 Oct 2025, ChengAo Shen, et al.

  • [Official Code - dmmv]

• TempoPFN: Synthetic Pre-training of Linear RNNs for Zero-shot Time Series Forecasting

  • 31 Oct 2025, Vladyslav Moroshan, et al.

• Selective Learning for Deep Time Series Forecasting

  • 29 Oct 2025, Yisong Fu, et al.

  • [Official Code - selective-learning]

• Quadratic Direct Forecast for Training Multi-Step Time-Series Forecast Models

  • 28 Oct 2025, Hao Wang, et al.

  • [Official Code - QDF]

• Not All Data are Good Labels: On the Self-supervised Labeling for Time Series Forecasting

  • 27 Oct 2025, Yuxuan Yang, et al.

  • [Official Code - SCAM]

• SwiftTS: A Swift Selection Framework for Time Series Pre-trained Models via Multi-task Meta-Learning

  • 27 Oct 2025, Tengxue Zhang, et al.

• DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting

  • 23 Oct 2025, Haonan Yang, et al.

  • [Official Code - DMSC]

• Abstain Mask Retain Core: Time Series Prediction by Adaptive Masking Loss with Representation Consistency

  • 22 Oct 2025, Renzhao Liang, et al.

  • [Official Code - AMRC]

• SEMPO: Lightweight Foundation Models for Time Series Forecasting

  • 22 Oct 2025, Hui He, et al.

  • [Official Code - SEMPO]

• Understanding the Implicit Biases of Design Choices for Time Series Foundation Models

  • 22 Oct 2025, Annan Yu, et al.

  • [Official Code - TSFM-Biases]

• Enhancing Time Series Forecasting through Selective Representation Spaces: A Patch Perspective

  • 20 Oct 2025, Xingjian Wu, et al.

  • [Official Code - SRSNet]

• Chronos-2: From Univariate to Universal Forecasting

  • 17 Oct 2025, Abdul Fatir Ansari, et al.

  • [Official Code - chronos-2]

• Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift

  • 16 Oct 2025, Zhiyuan Zhao, et al.

  • [Official Code - ShifTS]

• Time Series Foundation Models: Benchmarking Challenges and Requirements

  • 15 Oct 2025, Marcel Meyer, et al.

• Multi-Scale Finetuning for Encoder-based Time Series Foundation Models

  • 10 Oct 2025, Zhongzheng Qiao, et al.

  • [Official Code - MSFT]

• Benchmarking M-LTSF: Frequency and Noise-Based Evaluation of Multivariate Long Time Series Forecasting Models

  • 06 Oct 2025, Nick Janßen, et al.

• PhaseFormer: From Patches to Phases for Efficient and Effective Time Series Forecasting

  • 05 Oct 2025, Yiming Niu, et al.

  • [Official Code - PhaseFormer_TSL]

• Understanding Transformers for Time Series: Rank Structure, Flow-of-ranks, and Compressibility

  • 02 Oct 2025, Annan Yu, et al.

• U-Cast: Learning Hierarchical Structures for High-Dimensional Time Series Forecasting

  • 29 Sep 2025, Juntong Ni, et al.

  • [Official Code - Time-HD-Lib]

• Why Attention Fails: The Degeneration of Transformers into MLPs in Time Series Forecasting

  • 25 Sep 2025, Zida Liang, et al.

  • [Official Code - TST-Degeneration]

• DPANet: Dual Pyramid Attention Network for Multivariate Time Series Forecasting

  • 19 Sep 2025, Qianyang Li, et al.

  • [Official Code - DPANet]

• DAG: A Dual Causal Network for Time Series Forecasting with Exogenous Variables

  • 18 Sep 2025, Xiangfei Qiu, et al.

  • [Official Code - DAG]

• Super-Linear: A Lightweight Pretrained Mixture of Linear Experts for Time Series Forecasting

  • 18 Sep 2025, Liran Nochumsohn, et al.

  • [Official Code - SuperLinear]

• Text Reinforcement for Multimodal Time Series Forecasting

  • 31 Aug 2025, Chen Su, et al.

  • [Official Code - TeR-TSF]

• FinCast: A Foundation Model for Financial Time-Series Forecasting

  • 27 Aug 2025, Zhuohang Zhu, et al.

• FLAIRR-TS -- Forecasting LLM-Agents with Iterative Refinement and Retrieval for Time Series

  • 24 Aug 2025, Gunjan Jalori, et al.

• Interpreting Time Series Forecasts with LIME and SHAP: A Case Study on the Air Passengers Dataset

  • 17 Aug 2025, Manish Shukla, et al.

• Wavelet Mixture of Experts for Time Series Forecasting

  • 12 Aug 2025, Zheng Zhou, et al.

• From Values to Tokens: An LLM-Driven Framework for Context-aware Time Series Forecasting via Symbolic Discretization

  • 08 Aug 2025, Xiaoyu Tao, et al.

  • [Official Code - TokenCast]

• T3Time: Tri-Modal Time Series Forecasting via Adaptive Multi-Head Alignment and Residual Fusion

  • 06 Aug 2025, Abdul Monaf Chowdhury, et al.

  • [Official Code - T3Time]

• CMA: A Unified Contextual Meta-Adaptation Methodology for Time-Series Denoising and Prediction

  • 03 Aug 2025, Haiqi Jiang, et al.

  • [Official Code - CMA_KDD_2025]

• Enhancer: A Distribution-Aware Framework with Temporal-Relational Meta-Learning for Stock Prediction

  • 03 Aug 2025, Weijun Chen, et al.

• Tailored Forecasting from Short Time Series via Meta-learning

  • 31 Jul 2025, Declan A. Norton, et al.

• Multi-period Learning for Financial Time Series Forecasting

  • 20 Jul 2025, Xu Zhang, et al.

  • [Official Code - MLF]

• FLDmamba: Integrating Fourier and Laplace Transform Decomposition with Mamba for Enhanced Time Series Prediction

  • 17 Jul 2025, Qianru Zhang, et al.

• The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting

  • 17 Jul 2025, Lefei Shen, et al.

  • [Official Code - TSF_architecture]

• Fourier Basis Mapping: A Time-Frequency Learning Framework for Time Series Forecasting

  • 13 Jul 2025, Runze Yang, et al.

  • [Official Code - FBM-S]

• MoFE-Time: Mixture of Frequency Domain Experts for Time-Series Forecasting Models

  • 09 Jul 2025, Yiwen Liu, et al.

  • [Official Code - mofe-time]

• Non-collective Calibrating Strategy for Time Series Forecasting

  • 2 Jul 2025, Bin Wang, et al.

  • [Official Code - SoP]

• LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization

  • 01 Jul 2025, Wenzhe Niu, et al.

  • [Official Code - LangTime]

• The language of time: a language model perspective on time-series foundation models

  • 29 Jun 2025, Yi Xie, et al.

• Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs

  • 12 Jun 2025, Yucong Luo, et al.

  • [Official Code - Time-R1]

• TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting

  • 12 Jun 2025, Zhe Li, et al.

  • [Official Code - TSFM-Bench]

• Mamba time series forecasting with uncertainty quantification

  • 11 Jun 2025, Pedro Pessoa, et al.

  • [Official Code - Mamba-ProbTSF]

• Can Slow-thinking LLMs Reason Over Time? Empirical Studies in Time Series Forecasting

  • 10 Jun 2025, Jiahao Wang, et al.

  • [Official Code - TimeReasoner]

• Explore the Time Series Forecasting Potential of TabPFN Leveraging the Intrinsic Periodicity of Data

  • 10 Jun 2025, Sibo Cai, et al.

  • [Official Code - TabPFN-TSP]

• KARMA: A Multilevel Decomposition Hybrid Mamba Framework for Multivariate Long-Term Time Series Forecasting

  • 10 Jun 2025, Hang Ye, et al.

  • [Official Code - KARMA]

• LightGTS: A Lightweight General Time Series Forecasting Model

  • 06 Jun 2025, Yihang Wang, et al.

  • [Official Code - LightGTS]

• Timing is Important: Risk-aware Fund Allocation based on Time-Series Forecasting

  • 05 Jun 2025, Fuyuan Lyu, et al.

  • [Official Code - RTS-PnO]

• Winner-takes-all for Multivariate Probabilistic Time Series Forecasting

  • 05 Jun 2025, Adrien Cortés, et al.

  • [Official Code - timeMCL]

• Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal Narrative

  • 01 Jun 2025, Zihao Li, et al.

  • [Official Code - TaTS]

• IMTS is Worth Time × Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction

  • 30 May 2025, Zhangyi Hu, et al.

  • [Official Code - VIMTS]

• K2 VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting

  • 30 May 2025, Xingjian Wu, et al.

  • [Official Code - K2VAE]

• Sundial: A Family of Highly Capable Time Series Foundation Models

  • 30 May 2025, Yong Liu, et al.

  • [Official Code - Sundial]

• Improving Time Series Forecasting via Instance-aware Post-hoc Revision

  • 29 May 2025, Zhiding Liu, et al.

  • [Official Code - PIR]

• Less is More: Unlocking Specialization of Time Series Foundation Models via Structured Pruning

  • 29 May 2025, Lifan Zhao, et al.

• Explainable Multi-modal Time Series Prediction with LLM-in-the-Loop

  • 27 May 2025, Yushan Jiang, et al.

• TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state

  • 27 May 2025, Xiaowen Ma, et al.

  • [Official Code - TimePro]

• CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial Correlations

  • 25 May 2025, Haotian Si, et al.

  • [Official Code - CMoS]

• HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting

  • 23 May 2025, Boyuan Li, et al.

  • [Official Code - PyOmniTS]

• ReAugment: Model Zoo-Guided RL for Few-Shot Time Series Augmentation and Forecasting

  • 22 May 2025, Haochen Yuan, et al.

• Output Scaling: YingLong-Delayed Chain of Thought in a Large Pretrained Time Series Forecasting Model

  • 20 May 2025, Xue Wang, et al.

  • [Official Code - YingLong]

• TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting

  • 20 May 2025, Yifan Hu, et al.

  • [Official Code - TimeFilter]

• Non-stationary Diffusion For Probabilistic Time Series Forecasting

  • 19 May 2025, Weiwei Ye, et al.

  • [Official Code - NsDiff]

• Temporal Query Network for Efficient Multivariate Time Series Forecasting

  • 19 May 2025, Shengsheng Lin, et al.

  • [Official Code - TQNet]

• Intervention-Aware Forecasting: Breaking Historical Limits from a System Perspective

  • 16 May 2025, Zhijian Xu, et al.

  • [Official Code - TGTSF]

• OLinear: A Linear Model for Time Series Forecasting in Orthogonally Transformed Domain

  • 14 May 2025, Wenzhen Yue, et al.

  • [Official Code - OLinear]

• DELPHYNE: A Pre-Trained Model for General and Financial Time Series

  • 12 May 2025, Xueying Ding, et al.

• FilterTS: Comprehensive Frequency Filtering for Multivariate Time Series Forecasting

  • 07 May 2025, Yulong Wang, et al.

  • [Official Code - FilterTS]

• Retrieval Augmented Time Series Forecasting

  • 07 May 2025, Sungwon Han, et al.

  • [Official Code - RAFT]

• Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation

  • 06 May 2025, Chenxi Liu, et al.

  • [Official Code - TimeKD]

• FreDF: Learning to Forecast in the Frequency Domain

  • 06 May 2025, Hao Wang, et al.

  • [Official Code - FreDF]

• CASA: CNN Autoencoder-based Score Attention for Efficient Multivariate Long-term Time-series Forecasting

  • 04 May 2025, Minhyuk Lee, et al.

• A Closer Look at Transformers for Time Series Forecasting: Understanding Why They Work and Where They Struggle

  • 01 May 2025, Yu Chen, et al.

• Hi-Patch: Hierarchical Patch GNN for Irregular Multivariate Time Series

  • 01 May 2025, Yicheng Luo, et al.

  • [Official Code - Hi-Patch]

• ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and Reasoning

  • 16 Apr 2025, Zhe Xie, et al.

  • [Official Code - ChatTS]

• A Comprehensive Survey of Time Series Forecasting: Concepts, Challenges, and Future Directions

  • 10 Apr 2025, Mingyue Cheng, et al.

  • [Official Code - Awesome-Papers-Time-Series-Forecasting]

• ms-Mamba: Multi-scale Mamba for Time-Series Forecasting

  • 10 Apr 2025, Yusuf Meric Karadag, et al.

• Foundation Models for Time Series: A Survey

  • 05 Apr 2025, Siva Rama Krishna Kottapalli, et al.

• Integrating Quantum-Classical Attention in Patch Transformers for Enhanced Time Series Forecasting

  • 31 Mar 2025, Sanjay Chakraborty, et al.

  • [Official Code - QCAAPatchTF]

• TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment

  • 29 Mar 2025, Chenxi Liu, et al.

  • [Official Code - TimeCMA]

• BLAST: Balanced Sampling Time Series Corpus for Universal Forecasting Models

  • 27 May 2025, Zezhi Shao, et al.

  • [Official Code - BLAST]

• TSKANMixer: Kolmogorov-Arnold Networks with MLP-Mixer Model for Time Series Forecasting

  • 27 Mar 2025, Young-Chae Hong, et al.

• Towards Neural Scaling Laws for Time Series Foundation Models

  • 18 Mar 2025, Qingren Yao, et al.

  • [Official Code - TSFM-ScalingLaws]

• FreqMoE: Enhancing Time Series Forecasting through Frequency Decomposition Mixture of Experts

  • 16 Mar 2025, Ziqi Liu.

  • [Official Code - FreqMoE-main]

• ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables

  • 15 Mar 2025, Sebastian Pineda Arango, et al.

  • [Official Code - chronosx]

• Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting

  • 12 Mar 2025, Fuqiang Liu, et al.

  • [Official Code - AdvAttack_LLM4TS]

• Minimal Time Series Transformer

  • 12 Mar 2025, Joni-Kristian Kämäräinen

  • [Official Code - minimal_time_series_transformer]

• TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents

  • 10 Mar 2025, Geon Lee, et al.

• TS-LIF: A Temporal Segment Spiking Neuron Network for Time Series Forecasting

  • 07 Mar 2025, Shibo Feng, et al.

  • [Official Code - TS-LIF]

• TimeFound: A Foundation Model for Time Series Forecasting

  • 06 Mar 2025, Congxi Xiao, et al.

• Patch-wise Structural Loss for Time Series Forecasting

  • 02 Mar 2025, Dilfira Kudrat, et al.

  • [Official Code - PS_Loss]

• TimesBERT: A BERT-Style Foundation Model for Time Series Understanding

  • 28 Feb 2025, Haoran Zhang, et al

• Efficient Time Series Forecasting via Hyper-Complex Models and Frequency Aggregation

  • 27 Feb 2025, Eyal Yakir, et al.

• TimeKAN: KAN-based Frequency Decomposition Learning Architecture for Long-term Time Series Forecasting

  • 26 Feb 2025, Songtao Huang, et al.

  • [Official Code - TimeKAN]

• Amplifier: Bringing Attention to Neglected Low-Energy Components in Time Series Forecasting

  • 22 Feb 2025, Jingru Fei, et al.

  • [Official Code - Amplifier]

• TimePFN: Effective Multivariate Time Series Forecasting with Synthetic Data

  • 22 Feb 2025, Ege Onur Taga, et al.

  • [Official Code - TimePFN]

• TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation

  • 21 Feb 2025, Daoyu Wang, et al.

  • [Official Code - TimeDART]

• Adapting Large Language Models for Time Series Modeling via a Novel Parameter-efficient Adaptation Method

  • 19 Feb 2025, Juyuan Zhang, et al.

• AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting

  • 14 Feb 2025, Abdelhakim Benechehab, et al.

  • [Official Code - AdaPTS]

• Harnessing Vision Models for Time Series Analysis: A Survey

  • 13 Feb 2025, Jingchao Ni, et al.

  • [Official Code - awesome-vision-time-series]

• HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting

  • 12 Feb 2025, Shibo Feng, et al.

  • [Official Code - HDT]

• Are KANs Effective for Multivariate Time Series Forecasting?

  • 11 Feb 2025, Xiao Han, et al.

  • [Official Code - EasyTSF]

• xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition

  • 11 Feb 2025, Artyom Stitsyuk, et al.

  • [Official Code - xPatch]

• IN-Flow: Instance Normalization Flow for Non-stationary Time Series Forecasting

  • 06 Feb 2025, Wei Fan, et al.

• Error-quantified Conformal Inference for Time Series

  • 02 Feb 2025, Junxi Wu, et al.

  • [Official Code - Error-quantified-Conformal-Inference]

• FreEformer: Frequency Enhanced Transformer for Multivariate Time Series Forecasting

  • 23 Jan 2025, Wenzhen Yue, et al.

  • [Official Code - FreEformer]

• TVNet: A Novel Time Series Analysis Method Based on Dynamic Convolution and 3D-Variation

  • 23 Jan 2025, Chenghan Li, et al.

• TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting

  • 22 Jan 2025, Yifan Hu, et al.

  • [Official Code - TimeFilter]

• Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching

  • 14 Jan 2025, Meng Wang, et al.

• Battling the Non-stationarity in Time Series Forecasting via Test-time Adaptation

  • 09 Jan 2025, HyunGi Kim, et al.

  • [Official Code - TAFAS]

• The Tabular Foundation Model TabPFN Outperforms Specialized Time Series Forecasting Models Based on Simple Features

  • 09 Jan 2025, Shi Bin Hoo, et al.

  • [Official Code - tabpfn-time-series]

• Context-Alignment: Activating and Enhancing LLM Capabilities in Time Series

  • 07 Jan 2025, Yuxiao Hu, et al.

• LMS-AutoTSF: Learnable Multi-Scale Decomposition and Integrated Autocorrelation for Time Series Forecasting

  • 07 Jan 2025, Ibrahim Delibasoglu, et al.

  • [Official Code - LMS-TSF]

• Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences

  • 06 Jan 2025, Xiwen Chen, et al.

2024

• AverageLinear: Enhance Long-Term Time series forcasting with simple averaging

  • 30 Dec 2024, Gaoxiang Zhao, et al.

  • [Official Code - AverageLinear]

• TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting

  • 30 Dec 2024, Huanyu Zhang, et al.

• Unlocking the Power of Patch: Patch-Based MLP for Long-Term Time Series Forecasting

  • 25 Dec 2024, Peiwang Tang, et al.

• Hierarchical Classification Auxiliary Network for Time Series Forecasting

  • 24 Dec 2024, Yanru Sun, et al.

  • [Official Code - HCAN]

• DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting

  • 23 Dec 2024, Xiangfei Qiu, et al.

  • [Official Code - DUET]

• WPMixer: Efficient Multi-Resolution Mixing for Long-Term Time Series Forecasting

  • 22 Dec 2024, Md Mahmuddun Nabi Murad, et al.

  • [Official Code - WPMixer]

• TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation

  • 21 Dec 2024, Silin Yang, et al.

• Cherry-Picking in Time Series Forecasting: How to Select Datasets to Make Your Model Shine

  • 19 Dec 2024, Luis Roque, et al.

  • [Official Code - bench]

• CSformer: Combining Channel Independence and Mixing for Robust Multivariate Time Series Forecasting

  • 17 Dec 2024, Haoxin Wang, et al.

• LiNo: Advancing Recursive Residual Decomposition of Linear and Nonlinear Patterns for Robust Time Series Forecasting

  • 17 Dec 2024, Guoqi Yu, et al.

  • [Official Code - LiNo]

• TimeCHEAT: A Channel Harmony Strategy for Irregularly Sampled Multivariate Time Series Analysis

  • 17 Dec 2024, Jiexi Liu, et al.

  • [Official Code - TimeCHEAT]

• ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual Data

  • 16 Dec 2024, Chengsen Wang, et al.

  • [Official Code - ChatTime]

• ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis

  • 14 Dec 2024, Mingyue Cheng, et al.

  • [Official Code - ConvTimeNet]

• Auto-Regressive Moving Diffusion Models for Time Series Forecasting

  • 12 Dec 2024, Jiaxin Gao, et al.

  • [Official Code - ARMD]

• Rethinking Time Series Forecasting with LLMs via Nearest Neighbor Contrastive Learning

  • 06 Dec 2024, Jayanie Bogahawatte, et al.

• Disentangled Interpretable Representation for Efficient Long-term Time Series Forecasting

  • 26 Nov 2024, Yuang Zhao, et al.

  • [Official Code - DiPE-Linear]

• Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective

  • 13 Nov 2024, Chengsen Wang, et al.

  • [Official Code - GLAFF]

• Scaling Law for Time Series Forecasting

  • 09 Nov 2024, Jingzhe Shi, et al.

  • [Official Code - ScalingLawForTimeSeriesForecasting]

• EffiCANet: Efficient Time Series Forecasting with Convolutional Attention

  • 07 Nov 2024, Xinxing Zhou, et al.

• Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis

  • 07 Nov 2024, Qiang Wu, et al.

  • [Official Code - Peri-midFormer]

• From Similarity to Superiority: Channel Clustering for Time Series Forecasting

  • 06 Nov 2024, Jialin Chen, et al.

  • [Official Code - TimeSeriesCCM]

• A Mamba Foundation Model for Time Series Forecasting

  • 05 Nov 2024, Haoyu Ma, et al.

• Cross-Domain Pre-training with Language Models for Transferable Time Series Representations

  • 05 Nov 2024, Mingyue Cheng, et al.

  • [Official Code - CrossTimeNet]

• Not All Frequencies Are Created Equal:Towards a Dynamic Fusion of Frequencies in Time-Series Forecasting

  • 05 Nov 2024, Xingyu Zhang, et al.

  • [Offcial Code - FreDF]

• ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer

  • 04 Nov 2024, Jiawen Zhang, et al.

  • [Official Code - ElasTST]

• FilterNet: Harnessing Frequency Filters for Time Series Forecasting

  • 03 Nov 2024, Kun Yi, et al.

  • [Official Code - FilterNet]

• Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting

  • 31 Oct 2024, Zongjiang Shang, et al.

  • [Official Code - Ada-MSHyper]

• FlexTSF: A Universal Forecasting Model for Time Series with Variable Regularities

  • 30 Oct 2024, Jingge Xiao, et al.

  • [Official Code - FlexTSF]

• From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection

  • 30 Oct 2024, Xinlei Wang, et al.

  • [Official Code - From_News_to_Forecast]

• Sequential Order-Robust Mamba for Time Series Forecasting

  • 30 Oct 2024, Seunghan Lee, et al.

• LTBoost: Boosted Hybrids of Ensemble Linear and Gradient Algorithms for the Long-term Time Series Forecasting

  • 21 Oct 2024, Hubert Truchan, et al.

  • [Official Code - LTBoost]

• TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis

  • 21 Oct 2024, Shiyu Wang, et al.

  • [Official Code - TimeMixer]

• HiPPO-KAN: Efficient KAN Model for Time Series Analysis

  • 19 Oct 2024, SangJong Lee, et al.

• Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting

  • 16 Oct 2024, Jinliang Deng, et al.

• FoundTS: Comprehensive and Unified Benchmarking of Foundation Models for Time Series Forecasting

  • 15 Oct 2024, Zhe Li, et al.

• LLM-Mixer: Multiscale Mixing in LLMs for Time Series Forecasting

  • 15 Oct 2024, Md Kowsher, et al.

  • [Official Code - LLMMixer]

• Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts

  • 14 Oct 2024, Xu Liu, et al.

  • [Official Code - moirai-moe-1]

• Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shift

  • 13 Oct 2024, Yanru Sun, et al.

  • [Official Code - TFPS]

• Are Self-Attentions Effective for Time Series Forecasting?

  • 12 Oct 2024, Dongbin Kim, et al.

  • [Official Code - CATS]

• Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space Models

  • 12 Oct 2024, Sathya Kamesh Bhethanabhotla, et al.

  • [Official Code - Mamba4Cast]

• TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

  • 12 Oct 2024, Peiyuan Liu, et al.

  • [Official Code - TimeBridge]

• Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting

  • 08 Oct 2024, Qingxiang Liu, et al.

• Timer-XL: Long-Context Transformers for Unified Time Series Forecasting

  • 07 Oct 2024, Yong Liu, et al.

• Autoregressive Moving-average Attention Mechanism for Time Series Forecasting

  • 04 Oct 2024, Jiecheng Lu, et al.

  • [Official Code - ARMA-Attention]

• MMFNet: Multi-Scale Frequency Masking Neural Network for Multivariate Time Series Forecasting

  • 02 Oct 2024, Aitian Ma, et al.

• NuwaTS: a Foundation Model Mending Every Incomplete Time Series

  • 02 Oct 2024, Jinguo Cheng, et al.

  • [Official Code - NuwaTS]

• Frequency Adaptive Normalization For Non-stationary Time Series Forecasting

  • 30 Sep 2024, Weiwei Ye, et al.

  • [Official Code - FAN]

• Evolving Multi-Scale Normalization for Time Series Forecasting under Distribution Shifts

  • 29 Sep 2024, Dalin Qin, et al.

  • [Official Code - EvoMSN]

• CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns

  • 27 Sep 2024, Shengsheng Lin, et al.

  • [Official Code - CycleNet]

• CMamba: Channel Correlation Enhanced State Space Models for Multivariate Time Series Forecasting

  • 26 Sep 2024, Chaolv Zeng, et al.

  • [Official Code - CMamba]

• PGN: The RNN's New Successor is Effective for Long-Range Time Series Forecasting

  • 26 Sep 2024, Yuxin Jia, et al.

  • [Official Code - TPGN]

• Double-Path Adaptive-correlation Spatial-Temporal Inverted Transformer for Stock Time Series Forecasting

  • 24 Sep 2024, Wenbo Yan, et al.

• Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts

  • 24 Sep 2024, Xiaoming Shi, et al.

  • [Official Code - Time-MoE]

• D2Vformer: A Flexible Time Series Prediction Model Based on Time Position Embedding

  • 17 Sep 2024, Xiaobao Song, et al.

  • [Official Code - D2Vformer]

• TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model

  • 03 Sep 2024, Defu Cao, et al.

• VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters

  • 30 Aug 2024, Mouxiang Chen, et al.

  • [Official Code - VisionTS]

• Mamba or Transformer for Time Series Forecasting? Mixture of Universals (MoU) Is All You Need

  • 28 Aug 2024, Sijia Peng, et al.

  • [Official Code - mou]

• PRformer: Pyramidal Recurrent Transformer for Multivariate Time Series Forecasting

  • 20 Aug 2024, Yongbo Yu, et al.

  • [Official Code - PRformer]

• Unlocking the Power of LSTM for Long Term Time Series Forecasting

  • 19 Aug 2024, Yaxuan Kong, et al.

• Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators

  • 13 Aug 2024, Lifan Zhao, et al.

  • [Official Code - LIFT]

• Bidirectional Generative Pre-training for Improving Time Series Representation Learning

  • 11 Aug 2024, Ziyang Song, et al.

  • [Official Code - BiTimelyGPT]

• Scalable Transformer for High Dimensional Multivariate Time Series Forecasting

  • 08 Aug 2024, Xin Zhou, et al.

  • [Official Code - ScalableTransformer4HighDimensionMTSF]

• RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms

  • 06 Aug 2024, Luis Roque, et al.

  • [Official Code - robustness_hierarchical_time_series_forecasting_algorithms]

• Fine-grained Attention in Hierarchical Transformers for Tabular Time-series

  • 02 Aug 2024, Raphael Azorin, et al.

  • [Official Code - fieldy]

• HiMTM: Hierarchical Multi-Scale Masked Time Series Modeling with Self-Distillation for Long-Term Forecasting

  • 01 Aug 2024, Shubao Zhao, et al.

• DAM: Towards A Foundation Model for Time Series Forecasting

  • 25 Jul 2024, Luke Darlow, et al.

• A Survey of Explainable Artificial Intelligence (XAI) in Financial Time Series Forecasting

  • 22 Jul 2024, Pierre-Daniel Arsenault, et al.

• Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization

  • 18 Jul 2024, Yirui Liu, et al.

  • [Official Code - df2m]

• Deep Time Series Models: A Comprehensive Survey and Benchmark

  • 18 Jul 2024, Yuxuan Wang, et al.

  • [Official Code - Time-Series-Library]

• Long Input Sequence Network for Long Time Series Forecasting

  • 18 Jul 2024, Chao Ma, et al.

• Revisiting Attention for Multivariate Time Series Forecasting

  • 18 Jul 2024, Haixiang Wu, et al.

  • [Official Code - FSatten-SOatten]

• Large Pre-trained time series models for cross-domain Time series analysis tasks

  • 11 Jul 2024, Harshavardhan Kamarthi, et al.

• Loss Shaping Constraints for Long-Term Time Series Forecasting

  • 11 Jul 2024, Ignacio Hounie, et al.

• ViTime: A Visual Intelligence-Based Foundation Model for Time Series Forecasting

  • 10 Jul 2024, Luoxiao Yang, et al.

  • [Official Code - ViTime]

• S2IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting

  • 07 Jul 2024, Zijie Pan, et al.

  • [Official Code - S2IP-LLM]

• Fredformer: Frequency Debiased Transformer for Time Series Forecasting

  • 03 Jul 2024, Xihao Piao, et al.

  • [Official Code - Fredformer]

• Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling

  • 01 Jul 2024, Guoqi Yu, et al.

  • [Official Code - Leddam]

• Addressing Prediction Delays in Time Series Forecasting: A Continuous GRU Approach with Derivative Regularization

  • 29 Jun 2024, SheoYon Jhin, et al.

  • [Official Code - CONTIME]

• Deep Frequency Derivative Learning for Non-stationary Time Series Forecasting

  • 29 Jun 2024, Wei Fan, et al.

• SigKAN: Signature-Weighted Kolmogorov-Arnold Networks for Time Series

  • 25 Jun 2024, Hugo Inzirillo, et al.

  • [Official Code - SigKAN]

• Are Language Models Actually Useful for Time Series Forecasting?

  • 22 Jun 2024, Mingtian Tan, et al.

  • [Official Code - TS_Models]

• DeciMamba: Exploring the Length Extrapolation Potential of Mamba

  • 20 Jun 2024, Assaf Ben-Kish, et al.

  • [Official Code - DeciMamba]

• Understanding Different Design Choices in Training Large Time Series Models

  • 20 Jun 2024, Yu-Neng Chuang, et al.

  • [Official Code - ltsm]

• Omni-Dimensional Frequency Learner for General Time Series Analysis

  • 19 Jul 2024, Xianing Chen, et al.

• Foundation Models for Time Series Analysis: A Tutorial and Survey

  • 18 Jun 2024, Yuxuan Liang, et al.

• Generative Pretrained Hierarchical Transformer for Time Series Forecasting

  • 18 Jun 2024, Zhiding Liu, et al.

  • [Official Code - GPHT]

• ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons

  • 17 Jun 2024, Jiawen Zhang, et al.

  • [Official Code - ProbTS]

• LLMFactor: Extracting Profitable Factors through Prompts for Explainable Stock Movement Prediction

  • 16 Jun 2024, Meiyun Wang, et al.

• RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large Spatial-Temporal Data

  • 12 Jun 2024, Chin-Chia Michael Yeh, et al.

• SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion

  • 12 Jun 2024, Lu Han, et al.

  • [Official Code - SOFTS]

• Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis

  • 12 Jun 2024, Haoxin Liu, et al.

  • [Official Code - Time-MMD]

• A Survey on Diffusion Models for Time Series and Spatio-Temporal Data

  • 11 Jun 2024, Yiyuan Yang, et al.

  • [Official Code - Awesome-TimeSeries-SpatioTemporal-Diffusion-Model]

• Calibration of Time-Series Forecasting: Detecting and Adapting Context-Driven Distribution Shift

  • 11 Jun 2024, Mouxiang Chen, et al.

  • [Official Code - Calibration-CDS]

• When and How: Learning Identifiable Latent States for Nonstationary Time Series Forecasting

  • 07 Jun 2024, Zijian Li, et al.

• Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting

  • 06 Jun 2024, Yifan Hu, et al.

  • [Official Code - AMD]

• Kolmogorov-Arnold Networks for Time Series: Bridging Predictive Power and Interpretability

  • 04 Jun 2024, Kunpeng Xu, et al.

• Timer: Generative Pre-trained Transformers Are Large Time Series Models

  • 04 Jun 2024, Yong Liu, et al.

  • [Official Code - Large-Time-Series-Model]

• SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention

  • 03 Jun 2024, Romain Ilbert, et al.

  • [Official Code - samformer]

• SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters

  • 03 Jun 2024, Shengsheng Lin, et al.

  • [Official Code - SparseTSF]

• BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition

  • 30 May 2024, Shikai Fang, et al.

  • [Official Code - BayOTIDE]

• Efficient and Effective Time-Series Forecasting with Spiking Neural Networks

  • 29 May 2024, Changze Lv, et al.

  • [Official Code - SeqSNN]

• UNITS: A Unified Multi-Task Time Series Model

  • 29 May 2024, Shanghua Gao, et al.

  • [Official Code - UniTS]

• ForecastGrapher: Redefining Multivariate Time Series Forecasting with Graph Neural Networks

  • 28 May 2024, Wanlin Cai, et al.

• MambaTS: Improved Selective State Space Models for Long-term Time Series Forecasting

  • 26 May 2024, Xiuding Cai, et al.

  • [Official Code - MambaTS-pytorch]

• CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning

  • 23 May 2024, Peiyuan Liu, et al.

  • [Official Code - CALF]

• TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

  • 23 May 2024, Shiyu Wang, et al.

  • [Official Code - TimeMixer]

• GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing

  • 18 May 2024, Chengqing Yu, et al.

  • [Official Code - GinAR]

• Bi-Mamba+: Bidirectional Mamba for Time Series Forecasting

  • 17 May 2024, Aobo Liang, et al.

• DGCformer: Deep Graph Clustering Transformer for Multivariate Time Series Forecasting

  • 14 May 2024, Qinshuo Liu, et al.

• Multi-Scale Dilated Convolution Network for Long-Term Time Series Forecasting

  • 14 May 2024, Feifei Li, et al

• Kolmogorov-Arnold Networks (KANs) for Time Series Analysis

  • 14 May 2024, Cristian J. Vaca-Rubio, et al.

• TKAN: Temporal Kolmogorov-Arnold Networks

  • 12 May 2024, Remi Genet, et al.

  • [Official Code - TKAN]

• DTMamba : Dual Twin Mamba for Time Series Forecasting

  • 11 May 2024, Zexue Wu, et al.

• Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting

  • 10 May 2024, Tianxiang Zhan, et al.

  • [Official Code - TEFN]

• T-Rep: Representation Learning for Time Series using Time-Embeddings

  • 09 May 2024, Archibald Fraikin, et al.

  • [Official Code - T-Rep]

• A Survey of Time Series Foundation Models: Generalizing Time Series Representation with Large Language Model

  • 07 May 2024, Jiexia Ye, et al.

  • [Official Code - Awesome-TimeSeries-LLM-FM]

• TSLANet: Rethinking Transformers for Time Series Representation Learning

  • 06 May 2024, Emadeldeen Eldele, et al.

  • [Official Code - TSLANet]

• Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach

  • 02 May 2024, Weijia Zhang, et al.

• Integrating Mamba and Transformer for Long-Short Range Time Series Forecasting

  • 23 Apr 2024, Xiongxiao Xu, et al.

  • [Official Code - Mambaformer-in-Time-Series]

• Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values

  • 21 Apr 2024, Xiaodan Chen, et al.

  • [Official Code - BiTGraph]

• A decoder-only foundation model for time-series forecasting

  • 17 Apr 2024, Abhimanyu Das, et al.

  • [Official Code - timesfm]

• Towards Transparent Time Series Forecasting

  • 15 Apr 2024, Krzysztof Kacprzyk, et al.

• Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

  • 09 Apr 2024, Vijay Ekambaram, et al.

  • [Official Code - granite-tsfm]

• ATFNet: Adaptive Time-Frequency Ensembled Network for Long-term Time Series Forecasting

  • 08 Apr 2024, Hengyu Ye, et al.

  • [Official Code - ATFNet]

• OneShotSTL: One-Shot Seasonal-Trend Decomposition For Online Time Series Anomaly Detection And Forecasting

  • 04 Apr 2023, Xiao He, et al.

  • [Official Code - OneShotSTL]

• Is Mamba Effective for Time Series Forecasting?

  • 02 Apr 2024, Zihan Wang, et al.

  • [Official Code - S-D-Mamba]

• TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

  • 02 Apr 2024, Defu Cao, et al.

  • [Official Code - TEMPO]

• MambaMixer: Efficient Selective State Space Models with Dual Token and Channel Selection

  • 29 Mar 2024, Ali Behrouz, et al.

• TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods

  • 29 Mar 2024, Xiangfei Qiu, et al.

  • [Official Code - TFB]

• An Analysis of Linear Time Series Forecasting Models

  • 25 Mar 2024, William Toner, et al.

  • [Official Code - linear-forecasting]

• An End-to-End Structure with Novel Position Mechanism and Improved EMD for Stock Forecasting

  • 25 Mar 2024, Chufeng Li, et al.

  • [Official Code - ACEFormer]

• HDMixer: Hierarchical Dependency with Extendable Patch for Multivariate Time Series Forecasting

  • 24 Mar 2024, Qihe Huang, et al.

• Latent Diffusion Transformer for Probabilistic Time Series Forecasting

  • 24 Mar 2024, Shibo Feng, et al.

• StockMixer: A Simple Yet Strong MLP-Based Architecture for Stock Price Forecasting

  • 24 Mar 2024, Jinyong Fan, et al.

  • [Official Code - StockMixer]

• ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis

  • 22 Mar 2024, Donghao Luo, et al.

  • [Official Code - ModernTCN]

• SiMBA: Simplified Mamba-Based Architecture for Vision and Multivariate Time series

  • 22 Mar 2024, Badri N. Patro, et al.

  • [Official Code - simba]

• iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

  • 14 Mar 2024, Yong Liu, et al.

  • [Official Code - iTransformer]

• Self-Supervised Learning for Time Series: Contrastive or Generative?

  • 14 Mar 2024, Ziyu Liu, et al.

  • [Official Code - SSL_Comparison]

• TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecasting

  • 14 Mar 2024, Md Atik Ahamed, et al.

  • [Official Code - TimeMachine]

• TimeDRL: Disentangled Representation Learning for Multivariate Time-Series

  • 13 Mar 2024, Ching Chang, et al.

  • [Official Code - TimeDRL]

• Chronos: Learning the Language of Time Series

  • 12 Mar 2024, Abdul Fatir Ansari, et al.

  • [Official Code - chronos-forecasting]

• Multi-Patch Prediction: Adapting LLMs for Time Series Representation Learning

  • 10 Mar 2024, Yuxuan Bian, et al.

  • [Official Code - aLLM4TS]

• MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process

  • 09 Mar 2024, Xinyao Fan, et al.

  • [Official Code - MG-TSD]

• Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting

  • 08 Mar 2024, Muyao Wang, et al.

  • [Official Code - HTV_Trans]

• Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

  • 07 Mar 2024, Peng Chen, et al.

  • [Official Code - pathformer]

• Periodicity Decoupling Framework for Long-term Series Forecasting

  • 06 Mar 2024, Tao Dai, et al.

  • [Official Code - PDF]

• InjectTST: A Transformer Method of Injecting Global Information into Independent Channels for Long Time Series Forecasting

  • 05 Mar 2024, Ce Chi, et al.

• CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables

  • 04 Mar 2024, Jiecheng Lu, et al.

  • [Official Code - CATS]

• Diffusion-TS: Interpretable Diffusion for General Time Series Generation

  • 04 Mar 2024, Xinyu Yuan, et al.

  • [Official Code - Diffusion-TS]

• Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models

  • 29 Feb 2024, Kelvin Koa, et al.

  • [Official Code - SEP]

• TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables

  • 29 Feb 2024, Yuxuan Wang, et al.

  • [Official Code - TimeXer]

• UniTS: Building a Unified Time Series Model

  • 29 Feb 2024, Shanghua Gao, et al.

  • [Official Code - UniTS]

• TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis

  • 26 Feb 2024, Sabera Talukder, et al.

  • [Official Code - TOTEM]

• LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting

  • 25 Feb 2024, Haoxin Liu, et al.

  • [Official Code - lstprompt]

• Deep Coupling Network For Multivariate Time Series Forecasting

  • 23 Feb 2024, Kun Yi, et al.

• TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series

  • 22 Feb 2024, Chenxi Sun, et al.

  • [Official Code - TEST]

• CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting

  • 16 Feb 2024, Wang Xue, et al.

  • [Official Code - CARD]

• ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling

  • 16 Feb 2024, Yuqi Chen, et al.

  • [Official Code - ContiFormer]

• Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review

  • 15 Feb 2024, Jing Su, et al.

• Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

  • 08 Feb 2024, Kashif Rasul, et al.

  • [Official Code - lag-llama]

• MultiResFormer: Transformer with Adaptive Multi-Resolution Modeling for General Time Series Forecasting

  • 08 Feb 2024, Linfeng Du, et al.

• MOMENT: A Family of Open Time-series Foundation Models

  • 06 Feb 2024, Mononito Goswami, et al.

  • [Official Code - MOMENT]

• DiffsFormer: A Diffusion Transformer on Stock Factor Augmentation

  • 05 Feb 2024, Yuan Gao, et al.

• Position Paper: What Can Large Language Models Tell Us about Time Series Analysis

  • 05 Feb 2024, Ming Jin, et al.

• AutoTimes: Autoregressive Time Series Forecasters via Large Language Models

  • 04 Feb 2024, Yong Liu, et al.

  • [Official Code - AutoTimes]

• FreDF: Learning to Forecast in Frequency Domain

  • 04 Feb 2024, Hao Wang, et al.

  • [Official Code - FreDF]

• Unified Training of Universal Time Series Forecasting Transformers

  • 04 Feb 2024, Gerald Woo, et al.

  • [Official Code - uni2ts]

• RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies

  • 03 Feb 2024, Hao Cheng, et al.

  • [Official Code - RobustTSF]

• Large Language Models for Time Series: A Survey

  • 02 Feb 2024, Xiyuan Zhang, et al.

  • [Official Code - awesome-llm-time-series]

• A Survey of Deep Learning and Foundation Models for Time Series Forecasting

  • 25 Jan 2024, John A. Miller, et al.

• LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters

  • 18 Jan 2024, Ching Chang, et al.

• MSHyper: Multi-Scale Hypergraph Transformer for Long-Range Time Series Forecasting

  • 17 Jan 2024, Zongjiang Shang, et al.

• RWKV-TS: Beyond Traditional Recurrent Neural Network for Time Series Tasks

  • 17 Jan 2024, Haowen Hou, et al.

  • [Official Code - RWKV-TS]

• CNN Kernels Can Be the Best Shapelets

  • 16 Jan 2024, Eric Qu, et al.

• GAFormer: Enhancing Timeseries Transformers Through Group-Aware Embeddings

  • 16 Jan 2024, Jingyun Xiao, et al.

  • [Official Code - GAFormer]

• Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns

  • 16 Jan 2024, Hongbin Huang, et al.

• Interpretable Sparse System Identification: Beyond Recent Deep Learning Techniques on Time-Series Prediction

  • 16 Jan 2024, Xiaoyi Liu, et al.

• Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data

  • 16 Jan 2024, Ayesha Vermani, et al.

• Self-Supervised Contrastive Learning for Long-term Forecasting

  • 16 Jan 2024, Junwoo Park, et al.

  • [Official Code - Self-Supervised-Contrastive-Forecsating]

• SocioDojo: Building Lifelong Analytical Agents with Real-world Text and Time Series

  • 16 Jan 2024, Junyan Cheng, et al.

• Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting

  • 16 Jan 2024, Yuxin Li, et al.

• HiMTM: Hierarchical Multi-Scale Masked Time Series Modeling for Long-Term Forecasting

  • 10 Jan 2024, Shubao Zhao, et al.

• Universal Time-Series Representation Learning: A Survey

  • 08 Jan 2024, Patara Trirat, et al.

  • [Official Code - awesome-deep-time-series-representations]

• UnetTSF: A Better Performance Linear Complexity Time Series Prediction Model

  • 05 Jan 2024, Chu Li, et al.

  • [Official Code - UnetTSF]

• U-Mixer: An Unet-Mixer Architecture with Stationarity Correction for Time Series Forecasting

  • 04 Jan 2024, Xiang Ma, et al.

  • [Official Code - U-Mixer]

2023

• MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting

  • 31 Dec 2023, Wanlin Cai, et al.

  • [Official Code - MSGNet]

• Learning the Dynamic Correlations and Mitigating Noise by Hierarchical Convolution for Long-term Sequence Forecasting

  • 28 Dec 2023, Zhihao Yu, et al.

  • [Official Code - HMNet]

• TSPP: A Unified Benchmarking Tool for Time-series Forecasting

  • 28 Dec 2023, Jan Bączek, et al.

  • [Official Code - TimeSeriesPredictionPlatform]

• Continuous-time Autoencoders for Regular and Irregular Time Series Imputation

  • 27 Dec 2023, Hyowon Wi, et al.

• Learning to Embed Time Series Patches Independently

  • 27 Dec 2023, Seunghan Lee, et al.

  • [Official Code - pits]

• TimesURL: Self-supervised Contrastive Learning for Universal Time Series Representation Learning

  • 25 Dec 2023, Jiexi Liu, et al.

• AutoXPCR: Automated Multi-Objective Model Selection for Time Series Forecasting

  • 20 Dec 2023, Raphael Fischer, et al.

  • [Official Code - xpcr]

• CGS-Mask: Making Time Series Predictions Intuitive for All

  • 15 Dec 2023, Feng Lu, et al.

• Learning from Polar Representation: An Extreme-Adaptive Model for Long-Term Time Series Forecasting

  • 14 Dec 2023, Yanhong Li, et al.

  • [Official Code - DAN]

• SimPSI: A Simple Strategy to Preserve Spectral Information in Time Series Data Augmentation

  • 10 Dec 2023, Hyun Ryu, et al.

  • [Official Code - simpsi]

• Mamba: Linear-Time Sequence Modeling with Selective State Spaces

  • 01 Dec 2023, Albert Gu, et al.

  • [Official Code - mamba]

• Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting

  • 24 Nov 2023, Yong Liu, et al.

  • [Official Code - Nonstationary_Transformers]

• FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective

  • 10 Nov 2023, Kun Yi, et al.

  • [Official Code - FourierGNN]

• Frequency-domain MLPs are More Effective Learners in Time Series Forecasting

  • 10 Nov 2023, Kun Yi, et al.

  • [Official Code - FreTS]

• Multi-resolution Time-Series Transformer for Long-term Forecasting

  • 07 Nov 2023, Yitian Zhang, et al.

  • [Official Code - MTST]

• PT-Tuning: Bridging the Gap between Time Series Masked Reconstruction and Forecasting via Prompt Token Tuning

  • 07 Nov 2023, Hao Liu, et al.

• BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis

  • 31 Oct 2023, Zelin Ni, et al.

  • [Official Code - Basisformer]

• ProNet: Progressive Neural Network for Multi-Horizon Time Series Forecasting

  • 30 Oct 2023, Yang Lin

• Hierarchical Ensemble-Based Feature Selection for Time Series Forecasting

  • 26 Oct 2023, Ayşın Tümay, et al.

• Attention-Based Ensemble Pooling for Time Series Forecasting

  • 24 Oct 2023, Dhruvit Patel, et al.

  • [Official Code - denpool]

• Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series

  • 19 Oct 2023, Ioannis Nasios, et al.

  • [Official Code - M5_Uncertainty_3rd_place]

• A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis

  • 18 Oct 2023, Shuhan Zhong, et al.

  • [Official Code - MSD-Mixer]

• Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook

  • 16 Oct 2023, Ming Jin, et al.

  • [Official Code - awesome-timeseries-spatiotemporal-lm-llm]

• UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting

  • 15 Oct 2023, Xu Liu, et al.

  • [Official Code - UniTime]

• Counterfactual Explanations for Time Series Forecasting

  • 12 Oct 2023, Zhendong Wang, et al.

  • [Official Code - counterfactual-explanations-for-forecasting]

• Lag-Llama: Towards Foundation Models for Time Series Forecasting

  • 12 Oct 2023, Kashif Rasul, et al.

  • [Official Code - lag-llama]

• Large Language Models Are Zero-Shot Time Series Forecasters

  • 11 Oct 2023, Nate Gruver, et al.

  • [Official Code - llmtime]

• Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain

  • 08 Oct 2023, Gerald Woo, et al.

  • [Official Code - pretrain-time-series-cloudops]

• Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs

  • 04 Oct 2023, Ilan Naiman, et al.

• Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

  • 03 Oct 2023, Ming Jin, et al.

  • [Official Code - Time-LLM]

• Modality-aware Transformer for Time series Forecasting

  • 02 Oct 2023, Hajar Emami, et al.

• PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting

  • 01 Oct 2023, Zeying Gong, et al.

  • [Official Code - PatchMixer]

• Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective

  • 22 Sep 2023, Zhiding Liu, et al.

• OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling

  • 22 Sep 2023, Yi-Fan Zhang, et al.

  • [Official Code - OneNet]

• WFTNet: Exploiting Global and Local Periodicity in Long-term Time Series Forecasting

  • 20 Sep 2023, Peiyuan Liu, et al.

  • [Official Code - WFTNet]

• Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data

  • 11 Sep 2023, Yucheng Wang, et al.

  • [Official Code - FCSTGNN]

• PAITS: Pretraining and Augmentation for Irregularly-Sampled Time Series

  • 25 Aug 2023, Nicasia Beebe-Wang, et al.

  • [Official Code - irregular timeseries pretraining]

• TFDNet: Time-Frequency Enhanced Decomposed Network for Long-term Time Series Forecasting

  • 25 Aug 2023, Yuxiao Luo, et al.

  • [Official Code - TFDNet]

• Easy attention: A simple self-attention mechanism for transformer-based time-series reconstruction and prediction

  • 24 Aug 2023, Marcial Sanchis-Agudo, et al.

• Multi-scale Transformer Pyramid Networks for Multivariate Time Series Forecasting

  • 23 Aug 2023, Yifan Zhang, et al.

• SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

  • 22 Aug 2023, Shengsheng Lin, et al.

  • [Official Code - SegRNN]

• LLM4TS: Two-Stage Fine-Tuning for Time-Series Forecasting with Pre-Trained LLMs

  • 16 Aug 2023, Ching Chang, et al.

• PETformer: Long-term Time Series Forecasting via Placeholder-enhanced Transformer

  • 09 Aug 2023, Shengsheng Lin, et al.

• DSformer: A Double Sampling Transformer for Multivariate Time Series Long-term Prediction

  • 07 Aug 2023, Chengqing Yu, et al.

• Hierarchical Proxy Modeling for Improved HPO in Time Series Forecasting

  • 04 Aug 2023, Arindam Jati, et al.

• Unsupervised Representation Learning for Time Series: A Review

  • 03 Aug 2023, Qianwen Meng, et al.

  • [Official Code - ULTS]

• Automatic Feature Engineering for Time Series Classification: Evaluation and Discussion

  • 02 Aug 2023, Aurélien Renault, et al.

  • [Official Code - Automatic-Feature-Engineering-for-TSC]

• Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization Approach

  • 02 Aug 2023, Chunwei Yang, et al.

  • [Official Code - Floss]

• SimpleTS: An Efficient and Universal Model Selection Framework for Time Series Forecasting

  • 01 Aug 2023, Yuanyuan Yao, et al.

• DeepTSF: Codeless machine learning operations for time series forecasting

  • 28 Jul 2023, Sotiris Pelekis, et al.

  • [Official Code - DeepTSF]

• TimeGNN: Temporal Dynamic Graph Learning for Time Series Forecasting

  • 27 Jul 2023, Nancy Xu, et al.

  • [Official Code - Time-GNN]

• TransFusion: Generating Long, High Fidelity Time Series using Diffusion Models with Transformers

  • 24 Jul 2023, Md Fahim Sikder, et al.

  • [Official Code - TransFusion]

• Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting

  • 21 Jul 2023, Marcel Kollovieh, et al.

  • [Official Code - unconditional-time-series-diffusion]

• TimeTuner: Diagnosing Time Representations for Time-Series Forecasting with Counterfactual Explanations

  • 19 Jul 2023, Jianing Hao, et al.

  • [Official Code - TimeTuner]

• Look Ahead: Improving the Accuracy of Time-Series Forecasting by Previewing Future Time Features

  • 18 July 2023, Seonmin Kim, et al.

  • [Official Code - Look Ahead]

• GBT: Two-stage transformer framework for non-stationary time series forecasting

  • 17 Jul 2023, Li Shen, et al.

  • [Official Code - GBT-Neural_Networks_2023]

• Sequential Monte Carlo Learning for Time Series Structure Discovery

  • 13 Jul 2023, Feras A. Saad, et al.

  • [Official Code - AutoGP.jl]

• A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection

  • 07 Jul 2023, Ming Jin, et al.

  • [Official Code - Awesome-GNN4TS]

• GEANN: Scalable Graph Augmentations for Multi-Horizon Time Series Forecasting

  • 07 Jul 2023, Sitan Yang, et al.

• FITS: Modeling Time Series with 10k Parameters

  • 06 Jul 2023, Zhijian Xu, et al.

  • [Official Code - FITS]

• SAITS: Self-Attention-based Imputation for Time Series

  • 05 Jul 2023, Wenjie Du, et al.

  • [Official Code - SAITS]

• SageFormer: Series-Aware Graph-Enhanced Transformers for Multivariate Time Series Forecasting

  • 04 Jul 2023, Zhenwei Zhang, et al.

• ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection

  • 03 Jul 2023, Yuhang Chen, et al.

  • [Official Code - IMDiffusion]

• Precursor-of-Anomaly Detection for Irregular Time Series

  • 27 Jun 2023, SheoYon Jhin, et al.

  • [Official Code - PAD]

• Anomaly Detection with Score Distribution Discrimination

  • 26 Jun 2023, Minqi Jiang, et al.

  • [Official Code - Overlap]

• InParformer: Evolutionary Decomposition Transformers with Interactive Parallel Attention for Long-Term Time Series Forecasting

  • 26 Jun 2023, Haizhou Cao, et al.

• Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting

  • 19 Jun 2023, Xinli Yu, et al.

• DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection

  • 17 Jun 2023, Yiyuan Yang, et al.

  • [Official Code - KDD2023-DCdetector]

• MultiWave: Multiresolution Deep Architectures through Wavelet Decomposition for Multivariate Time Series Prediction

  • 16 Jun 2023, Iman Deznabi, et al.

  • [Official Code - MultiWave]

• Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects

  • 16 Jun 2023, Kexin Zhang, et al.

  • [Official Code - Awesome-SSL4TS]

• GCformer: An Efficient Framework for Accurate and Scalable Long-Term Multivariate Time Series Forecasting

  • 14 Jun 2023, YanJun Zhao, et al.

  • [Official Code - GCformer]

• TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting

  • 14 Jun 2023, Vijay Ekambaram, et al.

  • [Official Code - tsfm]

• Correlated Time Series Self-Supervised Representation Learning via Spatiotemporal Bootstrapping

  • 12 Jun 2023, Luxuan Wang, et al.

• Feature Programming for Multivariate Time Series Prediction

  • 09 Jun 2023, Alex Reneau, et al.

  • [Official Code - FeatureProgramming]

• Self-Interpretable Time Series Prediction with Counterfactual Explanations

  • 09 Jun 2023, Jingquan Yan, et al.

• Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations

  • 09 Jun 2023, Etienne Le Naour, et al.

• Non-autoregressive Conditional Diffusion Models for Time Series Prediction

  • 08 Jun 2023, Lifeng Shen, et al.

• Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency

  • 03 Jun 2023, Owen Queen, et al.

• DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

  • 03 Jun 2023, Salva Rühling Cachay, et al.

  • [Official Code - DYffusion]

• An End-to-End Time Series Model for Simultaneous Imputation and Forecast

  • 01 Jun 2023, Trang H. Tran, et al.

• Improving day-ahead Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context

  • 01 Jun 2023, Oussama Boussif, et al.

  • [Official Code - CrossViVit]

• Client: Cross-variable Linear Integrated Enhanced Transformer for Multivariate Long-Term Time Series Forecasting

  • 30 May 2023, Jiaxin Gao, et al.

  • [Official Code - Client]

• Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors

  • 30 May 2023, Yong Liu, et al.

  • [Official Code - Koopa]

• Learning Perturbations to Explain Time Series Predictions

  • 30 May 2023, Joseph Enguehard.

  • [Official Code - time_interpret]

• TLNets: Transformation Learning Networks for long-range time-series prediction

  • 25 May 2023, Wei Wang, et al.

  • [Official Code - TLNets]

• A Joint Time-frequency Domain Transformer for Multivariate Time Series Forecasting

  • 24 May 2023, Yushu Chen, et al.

  • [Official Code - JTFT]

• Forecasting Irregularly Sampled Time Series using Graphs

  • 22 May 2023, Vijaya Krishna Yalavarthi, et al.

  • [Official Code - GraFITi]

• Learning Structured Components: Towards Modular and Interpretable Multivariate Time Series Forecasting

  • 22 May 2023, Jinliang Deng, et al.

  • [Official Code - SCNN]

• Make Transformer Great Again for Time Series Forecasting: Channel Aligned Robust Dual Transformer

  • 20 May 2023, Wang Xue, et al.

• Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping

  • 18 May 2023, Zhe Li, et al.

  • [Official Code - RTSF]

• How Expressive are Spectral-Temporal Graph Neural Networks for Time Series Forecasting?

  • 11 May 2023, Ming Jin, et al.

• IVP-VAE: Modeling EHR Time Series with Initial Value Problem Solvers

  • 11 May 2023, Jingge Xiao, et al.

  • [Official Code - ivpvae]

• CUTS+: High-dimensional Causal Discovery from Irregular Time-series

  • 10 May 2023, Yuxiao Cheng, et al.

  • [Official Code - UNN]

• Causal Discovery from Subsampled Time Series with Proxy Variables

  • 09 May 2023, Mingzhou Liu, et al.

  • [Official Code - proxy_causal_discovery]

• Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction

  • 09 May 2023, Sheng Xiang, et al.

  • [Official Code - THGNN]

• Mlinear: Rethink the Linear Model for Time-series Forecasting

  • 08 May 2023, Wei Li, et al.

• Diffusion Models for Time Series Applications: A Survey

  • 01 May 2023, Lequan Lin, et al.

• Context Consistency Regularization for Label Sparsity in Time Series

  • 25 Apr 2023, Yooju Shin, et al.

  • [Official Code - CrossMatch]

• Prototype-oriented unsupervised anomaly detection for multivariate time series

  • 25 Apr 2023, Yuxin Li, et al.

  • [Official Code - PUAD]

• Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series

  • 25 Apr 2023, Aniruddh Raghu, et al.

  • [Official Code - SMD-SSL]

• Deep learning models for price forecasting of financial time series: A review of recent advancements: 2020-2022

  • 21 Apr 2023, Cheng Zhang, et al.

• Long-term Forecasting with TiDE: Time-series Dense Encoder

  • 17 Apr 2023, Abhimanyu Das, et al.

  • [Official Code - google-research - tide] [Unofficial Implementation - TiDE]

• Financial Time Series Forecasting using CNN and Transformer

  • 11 Apr 2023, Zhen Zeng, et al.

• The Capacity and Robustness Trade-off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecasting

  • 11 Apr 2023, Lu Han, et al.

  • [Official Code]

• Handling Concept Drift in Global Time Series Forecasting

  • 04 Apr 2023, Ziyi Liu, et al.

  • [Official Code]

• SimTS: Rethinking Contrastive Representation Learning for Time Series Forecasting

  • 31 Mar 2023, Xiaochen Zheng, et al.

  • [Official Code - SimTS_Representation_Learning]

• Towards Diverse and Coherent Augmentation for Time-Series Forecasting

  • 24 Mar 2023, Xiyuan Zhang, et al.

• UniTS: A Universal Time Series Analysis Framework with Self-supervised Representation Learning

  • 24 Mar 2023, Zhiyu Liang, et al.

  • [Official Code]

• Conformal Prediction for Time Series with Modern Hopfield Networks

  • 22 Mar 2023, Andreas Auer, et al.

  • [Official Code - HopCPT]

• Style Miner: Find Significant and Stable Explanatory Factors in Time Series with Constrained Reinforcement Learning

  • 21 Mar 2023, Dapeng Li, et al.

• Late Meta-learning Fusion Using Representation Learning for Time Series Forecasting

  • 20 Mar 2023, Terence L van Zyl.

  • [Official Code]

• Discovering Predictable Latent Factors for Time Series Forecasting

  • 18 Mar 2023, Jingyi Hou, et al.

  • [Official Code - discover_PLF]

• TSMixer: An All-MLP Architecture for Time Series Forecasting

  • 10 Mar 2023, Si-An Chen, et al.

  • [Official Code - tsmixer]

• PHILNet: A novel efficient approach for time series forecasting using deep learning

  • 08 Mar 2023, M.J. Jiménez-Navarro, et al.

  • [Official Code - PHILNet]

• Time Series Forecasting with Transformer Models and Application to Asset Management

  • 07 Mar 2023, Edmond Lezmi and Jiali Xu.

• Temporal Dependencies in Feature Importance for Time Series Predictions

  • 06 Mar 2023, Kin Kwan Leung, et al.

  • [Official Code - WinIT]

• Your time series is worth a binary image: machine vision assisted deep framework for time series forecasting

  • 28 Feb 2023, Luoxiao Yang, et al.

  • [Official Code - machine-vision-assisted-deep-time-series-analysis-MV-DTSA-]

• LightCTS: A Lightweight Framework for Correlated Time Series Forecasting

  • 23 Feb 2023, Zhichen Lai, et al.

  • [Official Code - lightcts]

• One Fits All:Power General Time Series Analysis by Pretrained LM

  • 23 Feb 2023, Tian Zhou, et al.

  • [Official Code - NeurIPS2023-One-Fits-All]

• Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting

  • 22 Feb 2023, Wei Fan, et al.

  • [Official Code]

• FormerTime: Hierarchical Multi-Scale Representations for Multivariate Time Series Classification

  • 20 Feb 2023, Mingyue Cheng, et al.

  • [Official Code]

• FrAug: Frequency Domain Augmentation for Time Series Forecasting

  • 18 Feb 2023, Muxi Chen, et al.

• Improved Online Conformal Prediction via Strongly Adaptive Online Learning

  • 15 Feb 2023, Aadyot Bhatnagar, et al.

  • [Official Code]

• SLOTH: Structured Learning and Task-based Optimization for Time Series Forecasting on Hierarchies

  • 11 Feb 2023, Fan Zhou, et al.

• MTS-Mixers: Multivariate Time Series Forecasting via Factorized Temporal and Channel Mixing

  • 09 Feb 2023, Zhe Li, et al.

  • [Official Code - MTS-Mixers]

• Domain Adaptation for Time Series Under Feature and Label Shifts

  • 06 Feb 2023, Huan He, et al.

  • [Official Code - Raincoat]

• Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting

  • 02 Feb 2023, Yunhao Zhang, Junchi Yan

  • [Official Code - Crossformer]

• MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting

  • 02 Feb 2023, Huiqiang Wang, et al.

  • [Official Code - MICN]

• SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling

  • 02 Feb 2023, Jiaxiang Dong, et al.

  • [Official Code - SimMTM]

• PrimeNet : Pre-Training for Irregular Multivariate Time Series

  • AAAI 2023, Ranak Roy Chowdhury, et al.

  • [Official Code]

• Learning Informative Representation for Fairness-aware Multivariate Time-series Forecasting: A Group-based Perspective

  • 27 Jan 2023, Hui He, et al.

• Improving Text-based Early Prediction by Distillation from Privileged Time-Series Text

  • 26 Jan 2023, Jinghui Liu, et al.

• Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series

  • 26 Jan 2023, Abdul Fatir Ansari, et al.

  • [Official Code - NCDSSM]

• Multi-view Kernel PCA for Time series Forecasting

  • 24 Jan 2023, Arun Pandey, et al.

• Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement

  • 08 Jan 2023, Yan Li, et al.

  • [Official Code]

• Towards Long-Term Time-Series Forecasting: Feature, Pattern, and Distribution

  • 05 Jan 2023, Yan Li, et al.

  • [Official Code]

• Infomaxformer: Maximum Entropy Transformer for Long Time-Series Forecasting Problem

  • 04 Jan 2023, Peiwang Tang, et al.

• Neural SDEs for Conditional Time Series Generation and the Signature-Wasserstein-1 metric

  • 03 Jan 2023, Pere Díaz Lozano, et al.

  • [Official Code]

2022

• End-to-End Modeling Hierarchical Time Series Using Autoregressive Transformer and Conditional Normalizing Flow based Reconciliation

  • 28 Dec 2022, Shiyu Wang, et al.

  • [Official Code]

• Dynamic Sparse Network for Time Series Classification: Learning What to "see"

  • 19 Dec 2022, Qiao Xiao, et al.

  • [Official Code]

• Contextually Enhanced ES-dRNN with Dynamic Attention for Short-Term Load Forecasting

  • 18 Dec 2022, Slawek Smyl, et al.

  • [Official Code]

• Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation

  • 16 Dec 2022, Yizhou Dang, et al.

  • [Official Code]

• First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting

  • 15 Dec 2022, Xiyuan Zhang, et al.

  • [Code]

• Put Attention to Temporal Saliency Patterns of Multi-Horizon Time Series

  • 15 Dec 2022, Nghia Duong-Trung, et al.

  • [Official Code]

• Area2Area Forecasting: Looser Constraints, Better Predictions (Manuscript submitted to journal Information Sciences)

  • [Official Code]

• Sequential Predictive Conformal Inference for Time Series

  • 07 Dec 2022, Chen Xu, et al.

  • [Official Code - SPCI-code]

• A K-variate Time Series Is Worth K Words: Evolution of the Vanilla Transformer Architecture for Long-term Multivariate Time Series Forecasting

  • 06 Dec 2022, Zanwei Zhou, et al.

  • [Official Code]

• DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting

  • 06 Dec 2022, Shiyong Lan, et al.

  • [Official Code]

• Learning of Cluster-based Feature Importance for Electronic Health Record Time-series

  • 06 Dec 2022, Henrique Aguiar, et al.

  • [Official Code]

• CoTMix: Contrastive Domain Adaptation for Time-Series via Temporal Mixup

  • 03 Dec 2022, Emadeldeen Eldele, et al.

  • [Official Code - CoTMix]

• FECAM: Frequency Enhanced Channel Attention Mechanism for Time Series Forecasting

  • 02 Dec 2022, Maowei Jiang, et al.

  • [Official Code]

• MHCCL: Masked Hierarchical Cluster-wise Contrastive Learning for Multivariate Time Series

  • 02 Dec 2022, Qianwen Meng, et al.

  • [Official Code]

• CRU: A Novel Neural Architecture for Improving the Predictive Performance of Time-Series Data

  • 30 Nov 2022, Sunghyun Sim, et al.

• AirFormer: Predicting Nationwide Air Quality in China with Transformers

  • 29 Nov 2022, Yuxuan Liang, et al.

  • [Official Code]

• Learning Latent Seasonal-Trend Representations for Time Series Forecasting

  • 29 Nov 2022, Zhiyuan Wang, et al.

  • [Official Code]

• A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

  • 27 Nov 2022, Yuqi Nie, et al.

  • [Official Code]

• A Comprehensive Survey of Regression Based Loss Functions for Time Series Forecasting

  • 05 Nov 2022, Aryan Jadon, et al.

  • [Official Code]

• Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion

  • 04 Nov 2022, Marin Biloš, et al.

• Multivariate Time-Series Forecasting with Temporal Polynomial Graph Neural Networks

  • 01 Nov 2022, Yijing Liu, et al.

• Time-Conditioned Dances with Simplicial Complexes: Zigzag Filtration Curve based Supra-Hodge Convolution Networks for Time-series Forecasting

  • 01 Nov 2022, Yuzhou Chen, et al.

• TILDE-Q: A Transformation Invariant Loss Function for Time-Series Forecasting

  • 26 Oct 2022, Hyunwook Lee, et al.

• WaveBound: Dynamic Error Bounds for Stable Time Series Forecasting

  • 25 Oct 2022, Youngin Cho, et al.

  • [Official Code]

• SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction

  • 13 Oct 2022, Minhao Liu, et al

  • [Official Code - SCINet]

• Koopman Neural Forecaster for Time Series with Temporal Distribution Shifts

  • 07 Oct 2022, Rui Wang, et al.

  • [Official Code]

• TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis

  • 05 Oct 2022, Haixu Wu, et al.

  • [Official Code]

• Retrieval Based Time Series Forecasting

  • 27 Sep 2022, Baoyu Jing, et al.

• FDNet: Focal Decomposed Network for Efficient, Robust and Practical Time Series Forecasting

  • 22 Sep 2022, Li Shen, et al.

  • [Official Code]

• PromptCast: A New Prompt-based Learning Paradigm for Time Series Forecasting

  • 20 Sep 2022, Hao Xue, et al.

  • [Official Code - PISA]

• Out-of-Distribution Representation Learning for Time Series Classification

  • 15 Sep 2022, Wang Lu, et al.

  • [Official Code]

• Statistical, machine learning and deep learning forecasting methods: Comparisons and ways forward

  • 05 Sep 2022, Spyros Makridakis, et al.

• Expressing Multivariate Time Series as Graphs with Time Series Attention Transformer

  • 19 Aug 2022, William T. Ng, et al.

  • [Official Code]

• Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models

  • 19 Aug 2022, Juan Miguel Lopez Alcaraz, et al.

  • [Official Code - SSSD]

• Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting

  • 14 Aug 2022, Zezhi Shao, et al.

  • [Official Code]

• Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting

  • 10 Aug 2022, Zezhi Shao, et al.

  • [Official Code]

• Respecting Time Series Properties Makes Deep Time Series Forecasting Perfect

  • 22 Jul 2022, Li Shen, et al.

  • [Official Code]

• Formal Algorithms for Transformers

  • 19 Jul 2022, Mary Phuong, Marcus Hutter

• Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms

  • 19 Jul 2022, Linbo Liu, et al.

  • [Official Code - gluonts]

• Generalizable Memory-driven Transformer for Multivariate Long Sequence Time-series Forecasting

  • 16 Jul 2022, Xiaoyun Zhao, et al.

  • [Official Code - CLMFormer]

• Learning Deep Time-index Models for Time Series Forecasting

  • 13 Jul 2022, Gerald Woo, et al.

  • [Official Code - DeepTime]

• Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes

  • 13 Jul 2022, Gregory Benton, et al.

  • [Official Code]

• Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

  • 04 Jul 2022, Tianping Zhang, et al.

• CATN: Cross Attentive Tree-Aware Network for Multivariate Time Series Forecasting

  • 28 Jun 2022, Hui He, et al.

• Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting

  • 28 Jun 2022, Junchen Ye, et al

  • [Official Code - ESG]

• Utilizing Expert Features for Contrastive Learning of Time-Series Representations

  • 23 Jun 2022, Manuel Nonnenmacher, et al.

  • [Official Code]

• Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency

  • 17 Jun 2022, Xiang Zhang, et al.

  • [Official Code]

• Closed-Form Diffeomorphic Transformations for Time Series Alignment

  • 16 Jun 2022, Iñigo Martinez, et al.

  • [Official Code]

• Contrastive Learning for Unsupervised Domain Adaptation of Time Series

  • 13 Jun 2022, Yilmazcan Ozyurt, et al.

  • [Official Code]

• Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting

  • 08 Jun 2022, Amin Shabani, et al.

  • [[Official Code](https: