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

Yu Chen; Nathalia Céspedes; Payam Barnaghi

2025 ICML ICML 2025

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

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Data Science & Analytics

Authors

Yu Chen, Nathalia Céspedes, Payam Barnaghi

Topics

Machine Learning > Core Methods > Representation Learning Deep Learning > Architectures > Transformers Data Science & Analytics > Methods > Time Series Analysis

Keywords

skip connection z-score normalization stationary intra-variate dependencies point-wise transformers self-dependent

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