awesome-time-series
github.com/cuge1995/awesome-time-series ↗list of papers, code, and other resources
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M4-competitionKaggle-time-series-competitionPapersConferencesTheory-ResourceCode-ResourceDatasets
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me 2020 resources from awesome-time-series"
Installation instructions →What's inside
Code-Resource
- A collection of time series prediction methods: rnn, seq2seq, cnn, wavenet, transformer, unet, n-beats, gan, kalman-filter
- A curated list of awesome time series databases, benchmarks and papers
- A Python toolkit for rule-based/unsupervised anomaly detection in time series
- ARCH models in Python
- A scikit-learn compatible Python toolbox for machine learning with time series
- A statistical library designed to fill the void in Python's time series analysis capabilities
Papers
- Active Model Selection for Positive Unlabeled Time Series Classification2020
- Adjusting for Autocorrelated Errors in Neural Networks for Time Series2021
- Adversarial Sparse Transformer for Time Series Forecasting2020
- A machine learning approach for forecasting hierarchical time series2021
- An Industry Case of Large-Scale Demand Forecasting of Hierarchical Components2020
- Anomaly detection for Cybersecurity: time series forecasting and deep learning2020
M4-competition
Datasets
Theory-Resource
Showing a sample of 149 resources. View the full list on GitHub →