philipperemy/keras-tcn

Health v2 · maintenance only

Adoption not part of the score

2012 stars · 462 forks observed · 2026-08-28

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

A Keras/TensorFlow implementation of Temporal Convolutional Networks (TCN) with dilated causal convolutions, usable as a drop-in layer alternative to LSTM/GRU. It supports Python and R and is actively tested against recent TensorFlow releases.

Use cases

• build temporal convolutional networks in keras
• replace lstm with tcn for long time series
• sequence classification with dilated causal convolutions
• time series forecasting model in tensorflow
• train tcn on gpu with tensorflow-metal on macos
• use tcn layer in r with keras

When to choose

• you need long-memory sequence modeling with stable gradients and parallel training
• you want a Keras layer that swaps in for LSTM/GRU
• you work in Python or R with TensorFlow 2.x

When to avoid

• you need PyTorch or JAX instead of TensorFlow/Keras
• your sequences are short and an LSTM suffices
• you need pretrained models rather than a layer implementation

Facets

library · maturity active

deep-learning machine-learning deep-learning machine-learning time-series python keras tcn temporal-convolutional-network tensorflow sequence-modeling r-language gpu

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