SequeL: A Continual Learning Library in PyTorch and JAX
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Abstract (arXiv)
Continual Learning is an important and challenging problem in machine learning, where models must adapt to a continuous stream of new data without forgetting previously acquired knowledge. While existing frameworks are built on PyTorch, the rising popularity of JAX might lead to divergent codebases, ultimately hindering reproducibility and progress. To address this problem, we introduce SequeL, a flexible and extensible library for Continual Learning that supports both PyTorch and JAX frameworks. SequeL provides a unified interface for a wide range of Continual Learning algorithms, including regularization-based approaches, replay-based approaches, and hybrid approaches. The library is designed towards modularity and simplicity, making the API suitable for both researchers and practitioners. We release SequeLfootnoteurlhttps://github.com/nik-dim/sequel as an open-source library, enabling researchers and developers to easily experiment and extend the library for their own purposes.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 23 of its 37 references that are in the map. First posted on arXiv 21 Apr 2023.
Builds on
23 of 37 references.
References · 23
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- 2017Gradient Episodic Memory for Continual Learningcited by 1,898
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- 2018Efficient Lifelong Learning with A-GEMcited by 1,058
- 2020Dark Experience for General Continual Learning: a Strong, Simple Baselinecited by 911
11 more
- 2016FractalNet: Ultra-Deep Neural Networks without Residualscited by 216
- 2020fastai: A Layered API for Deep Learningcited by 183
- 2020Understanding the Role of Training Regimes in Continual Learningcited by 180
- 2020Linear Mode Connectivity in Multitask and Continual Learningcited by 145
- 2021Avalanche: an End-to-End Library for Continual Learningcited by 124
- 2021Continuum: Simple Management of Complex Continual Learning Scenarioscited by 33
- 2020Accelerator-aware Neural Network Design using AutoMLcited by 30
- 2017Less-forgetful Learning for Domain Expansion in Deep Neural Networkscited by 27
- 2021Kernel Continual Learningcited by 27
- 2021Sequoia: A Software Framework to Unify Continual Learning Researchcited by 19
- 2022Avalanche RL: a Continual Reinforcement Learning Librarycited by 4
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Citing papers per year: 2023: 1.
1 paper.