| Efficient Automated Deep Learning for Time Series Forecasting | May 11, 2022 | AutoMLBayesian Optimization | CodeCode Available | 4 | 5 |
| Sundial: A Family of Highly Capable Time Series Foundation Models | Feb 2, 2025 | Representation LearningTime Series | CodeCode Available | 4 | 5 |
| Are Transformers Effective for Time Series Forecasting? | May 26, 2022 | Anomaly DetectionRelation Extraction | CodeCode Available | 4 | 5 |
| TimeGPT-1 | Oct 5, 2023 | Deep LearningTime Series | CodeCode Available | 4 | 5 |
| ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and Reasoning | Dec 4, 2024 | AttributeTime Series | CodeCode Available | 3 | 5 |
| Meta-Transformer: A Unified Framework for Multimodal Learning | Jul 20, 2023 | Time Series | CodeCode Available | 3 | 5 |
| Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting | Oct 12, 2023 | DecoderProbabilistic Time Series Forecasting | CodeCode Available | 3 | 5 |
| MixLinear: Extreme Low Resource Multivariate Time Series Forecasting with 0.1K Parameters | Oct 2, 2024 | Multivariate Time Series ForecastingTime Series | CodeCode Available | 3 | 5 |
| AER: Auto-Encoder with Regression for Time Series Anomaly Detection | Dec 27, 2022 | Anomaly DetectionBenchmarking | CodeCode Available | 3 | 5 |
| Intervention-Aware Forecasting: Breaking Historical Limits from a System Perspective | May 22, 2024 | Data IntegrationSensitivity | CodeCode Available | 3 | 5 |
