GenAI for time series modelling
Resources
Code
- #CODE Nixtla/nixtla: TimeGPT-1
- production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code ๐
- #CODE amazon-science/chronos-forecasting
- Chronos: Pretrained (Language) Models for Probabilistic Time Series Forecasting (github.com)
- #CODE thuml/Time-Series-Library: A Library for Advanced Deep Time Series Models. (github.com)
- TSLib is an open-source library for deep learning researchers, especially for deep time series analysis.
- #CODE Uni2TS
- Uni2TS is a PyTorch based library for research and applications related to Time Series Forecasting. It provides a unified framework for large-scale pre-training, fine-tuning, inference, and evaluation of Universal Time Series Transformers.
References
- #PAPER TimesNet TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis (2023)
- #PAPER Chronos Chronos: Learning the Language of Time Series (2024)
- #PAPER TimesFM A decoder-only foundation model for time-series forecasting (2024)
- #PAPER MOMENT MOMENT: A Family of Open Time-series Foundation Models (2024)
- #PAPER TimeGPT TimeGPT-1 (2024)
- #PAPER Agentic Retrieval-Augmented Generation for Time Series Analysis (2024)
- #PAPER Unified Training of Universal Time Series Forecasting Transformers (2024)
- Moirai by Salesforce
- Moirai: A Time Series Foundation Model for Universal Forecasting
- #PAPER Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts (2024)