zalandoresearch/pytorch-ts

Health v2 · maintenance only

Adoption not part of the score

1370 stars · 197 forks observed · 2026-08-28

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

PyTorchTS is a PyTorch-based probabilistic time series forecasting library that uses GluonTS as its backend API for loading, transforming, and backtesting time series datasets. It provides state-of-the-art models such as DeepAR, LSTNet, and N-BEATS implemented in PyTorch.

Use cases

• forecast future values of a time series with probabilistic predictions
• train a DeepAR model on hourly or minute-level data
• backtest time series forecasting models
• compare DeepAR, LSTNet, and N-BEATS on the same dataset
• run forecasting models on GPU with PyTorch
• predict demand or traffic from historical time series data

When to choose

• you want probabilistic time series forecasts in PyTorch
• you already use GluonTS but prefer PyTorch over MXNet
• you need models like DeepAR, LSTNet, or N-BEATS with a consistent API

When to avoid

• you need actively developed features or frequent updates
• you want a non-probabilistic point-forecast-only library
• you work outside the Python/PyTorch ecosystem

Facets

library · maturity maintenance

machine-learning deep-learning data-science machine-learning deep-learning time-series data-science python cross-platform pytorch time-series-forecasting probabilistic-forecasting gluonts deepar n-beats lstnet gpu

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