GMvandeVen/continual-learning resource

Health v2 · maintenance only

Adoption not part of the score

1879 stars · 345 forks observed · 2026-08-28

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

A PyTorch research codebase implementing many continual learning methods (EWC, SI, LwF, XdG, replay variants, iCaRL, generative classifier, etc.) across task-, domain-, and class-incremental scenarios. It accompanies the Nature Machine Intelligence article 'Three types of incremental learning' and related tutorials and blog posts.

Use cases

• reproduce continual learning experiments from papers
• compare continual learning methods like EWC, SI, and LwF
• run task-incremental learning on Split MNIST
• experiment with class-incremental learning scenarios
• learn how generative replay works in continual learning
• benchmark lifelong learning algorithms in PyTorch

When to choose

• you need reference implementations of many continual learning algorithms in one codebase
• you want to reproduce results from the 'Three types of incremental learning' paper
• you are studying or teaching lifelong/incremental learning with neural networks

When to avoid

• you need a production-ready continual learning library with stable APIs
• you want continual learning for non-classification tasks like NLP or detection
• you need support for very large-scale datasets or distributed training

Facets

learning-resource · maturity active

deep-learning machine-learning deep-learning machine-learning artificial-intelligence python continual-learning lifelong-learning incremental-learning pytorch research-code replay elastic-weight-consolidation generative-replay

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