time-series-transformers-review

Why we included this project

Anyone getting into transformer-based time series modeling will find this list saves them a lot of searching. It groups papers, code, and datasets by application area, so forecasting, anomaly detection, classification, and imputation work sit side by side instead of scattered across search results. Each entry links to the official paper and, when the authors released it, the code, which makes it easy to reproduce results or weigh one architecture against another. A companion survey and a taxonomy of transformer designs help newcomers see how the models developed and how they relate. For researchers and engineers who would rather learn from what has already been tried than rediscover it, this works well as a standing reference.