thuml/TimesNet

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1111 stars · 90 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

TimesNet is the official code release for the ICLR 2023 paper on temporal 2D-variation modeling for general time series analysis. It transforms 1D time series into 2D space to handle forecasting, imputation, anomaly detection, and classification, with complete code now merged into the Time-Series-Library repository.

Use cases

• forecast long-term and short-term time series
• detect anomalies in time series data
• impute missing values in time series
• classify time series signals
• benchmark time series models against baselines
• reproduce TimesNet paper results

When to choose

• you need a general-purpose deep learning model for multiple time series tasks
• you want state-of-the-art baselines for time series research
• you want to build on 2D-variation time series modeling via Time-Series-Library

When to avoid

• you need actively developed standalone code - use the Time-Series-Library repo instead
• you need simple statistical forecasting rather than deep learning
• you work outside time series analysis

Facets

library · maturity maintenance

machine-learning deep-learning data-science time-series machine-learning deep-learning data-science python time-series-forecasting anomaly-detection imputation classification research-code iclr-2023 pytorch gpu

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