AI for Time Series : Volume 2: Building Robust and Generalizable Models (Paperback)

Section 1 Introduction on AI for Time Series Analysis 1. Introduction Chapter ? Domain Adaptation and Foundation Models Section 2 AI for General Time Series Analysis 2. TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis 3. TSLANet: Rethinking Transformers for Time Series Representation Learning Section 3 AI for Distribution Shift in Time Series 4. OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling 5. SEA++: Multi-Graph-based Higher-Order Sensor Alignment for Multivariate Time-Series Unsupervised Domain Adaptation 6. AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data Section 4 Time Series Foundation Models 7. Time-LLM: Time Series Forecasting by Reprogramming Large Language Models 8. LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization 9. Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting 10. Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts 11. EEG Foundation Model 12. PHM Foundation Model

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