Awesome resources focus on the application of cutting-edge AI technologies for time-series analysis (AI4TS). They delve into advanced topics such as self-supervised learning (SSL), Graph Neural Networks for Time Series (GNN4TS), Large Language Models for Time Series (LLM4TS), Diffusion models, Mixture-of-Experts (MoE) architectures and Mamba models, Kolmogorov Arnold Networks (KAN), Learn at Test Time (TTT) among others. These resources span various domains, including healthcare, finance, and traffic, offering a comprehensive view of the field. In addition, they feature top-notch tutorials, courses, and workshops from prestigious conferences, hosted by globally renowned scholars and research teams. Whether you're a professional, data scientist, or researcher, these tools and techniques can significantly enhance your time-series data analysis capabilities, providing a clear roadmap for your studies.
Forecasting
Anomaly Detection
Imputation
Classification
Spatio-temporal prediction
One Fits all
Discussion
Reasoning
Representation learning(self-supervised learning && Semi-supervised learning&&Supervised learning)
Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification TPAMI 13 Aug 2022 CA-TCC
Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey ACM Computing Surveys, 2023
Label-efficient Time Series Representation Learning: A Review 13 Feb 2023
Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects 16 Jun 2023 SSL4TS
Unsupervised Representation Learning for Time Series: A Review 3 Aug 2023 ULTS
Self-Supervised Learning for Time Series: Contrastive or Generative? AI4TS workshop at IJCAI 2023 SSL_Comparison
Self-Supervised Contrastive Learning for Medical Time Series: A Systematic Review Sensors in 2023 Contrastive-Learning-in-Medical-Time-Series-Survey
Applications of Self-Supervised Learning to Biomedical Signals: where are we now post date 2023-04-11
What Constitutes Good Contrastive Learning in Time-Series Forecasting? last revised 13 Aug 2023
A review of self-supervised learning methods in the field of ECG 2023
Universal Time-Series Representation Learning: A Survey 8 Jan 2024 itouchz/awesome-deep-time-series-representations
Deep Learning for Trajectory Data Management and Mining: A Survey and Beyond 21 Mar 2024 yoshall/Awesome-Trajectory-Computing
Scaling-laws for Large Time-series Models 22 May 2024
Deep Time Series Forecasting Models: A Comprehensive Survey Mathematics 2024
GNN4TS
Generative models
General
Diffusion4TS
LLM4TS
Foundation && Pre-Trained models
A Survey on Time-Series Pre-Trained Models 18 May 2023 time-series-ptms
Toward a Foundation Model for Time Series Data 21 Oct 2023 code
A Review for Pre-Trained Transformer-Based Time Series Forecasting Models ITMS2023
A Survey of Deep Learning and Foundation Models for Time Series Forecasting 25 Jan 2024
Foundation Models for Time Series Analysis: A Tutorial and Survey 21 Mar 2024
Heterogeneous Contrastive Learning for Foundation Models and Beyond 30 Mar 2024
A Comprehensive Survey of Large Language Models and Multimodal Large Language Models in Medicine 14 May 2024
Application
latest
Chinese
HuiguangHe - Chinese Academy of Sciences, Institute of Automation
Bao-Liang Lu - Home Page
DongruiWu - Huazhong University of Science and Technology, Brain-Computer Interface and Machine Learning Lab
Yang Yang - Zhejiang University
Shenda Hong - Personal Homepage
Xiang Zhang Personal Homepage
54 commits
Awesome resources focus on the application of cutting-edge AI technologies for time-series analysis (AI4TS). They delve into advanced topics such as self-supervised learning (SSL), Graph Neural Networks for Time Series (GNN4TS), Large Language Models for Time Series (LLM4TS), Diffusion models, Mixture-of-Experts (MoE) architectures and Mamba models, Kolmogorov Arnold Networks (KAN), Learn at Test Time (TTT) among others. These resources span various domains, including healthcare, finance, and traffic, offering a comprehensive view of the field. In addition, they feature top-notch tutorials, courses, and workshops from prestigious conferences, hosted by globally renowned scholars and research teams. Whether you're a professional, data scientist, or researcher, these tools and techniques can significantly enhance your time-series data analysis capabilities, providing a clear roadmap for your studies.
Forecasting
Anomaly Detection
Imputation
Classification
Spatio-temporal prediction
One Fits all
Discussion
Reasoning
Representation learning(self-supervised learning && Semi-supervised learning&&Supervised learning)
Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification TPAMI 13 Aug 2022 CA-TCC
Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey ACM Computing Surveys, 2023
Label-efficient Time Series Representation Learning: A Review 13 Feb 2023
Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects 16 Jun 2023 SSL4TS
Unsupervised Representation Learning for Time Series: A Review 3 Aug 2023 ULTS
Self-Supervised Learning for Time Series: Contrastive or Generative? AI4TS workshop at IJCAI 2023 SSL_Comparison
Self-Supervised Contrastive Learning for Medical Time Series: A Systematic Review Sensors in 2023 Contrastive-Learning-in-Medical-Time-Series-Survey
Applications of Self-Supervised Learning to Biomedical Signals: where are we now post date 2023-04-11
What Constitutes Good Contrastive Learning in Time-Series Forecasting? last revised 13 Aug 2023
A review of self-supervised learning methods in the field of ECG 2023
Universal Time-Series Representation Learning: A Survey 8 Jan 2024 itouchz/awesome-deep-time-series-representations
Deep Learning for Trajectory Data Management and Mining: A Survey and Beyond 21 Mar 2024 yoshall/Awesome-Trajectory-Computing
Scaling-laws for Large Time-series Models 22 May 2024
Deep Time Series Forecasting Models: A Comprehensive Survey Mathematics 2024
GNN4TS
Generative models
General
Diffusion4TS
LLM4TS
Foundation && Pre-Trained models
A Survey on Time-Series Pre-Trained Models 18 May 2023 time-series-ptms
Toward a Foundation Model for Time Series Data 21 Oct 2023 code
A Review for Pre-Trained Transformer-Based Time Series Forecasting Models ITMS2023
A Survey of Deep Learning and Foundation Models for Time Series Forecasting 25 Jan 2024
Foundation Models for Time Series Analysis: A Tutorial and Survey 21 Mar 2024
Heterogeneous Contrastive Learning for Foundation Models and Beyond 30 Mar 2024
A Comprehensive Survey of Large Language Models and Multimodal Large Language Models in Medicine 14 May 2024
Application
latest
Chinese
HuiguangHe - Chinese Academy of Sciences, Institute of Automation
Bao-Liang Lu - Home Page
DongruiWu - Huazhong University of Science and Technology, Brain-Computer Interface and Machine Learning Lab
Yang Yang - Zhejiang University
Shenda Hong - Personal Homepage
Xiang Zhang Personal Homepage
54 commits