Avalanche: An End-to-End Library for Continual Learning

Abstract

Learning continually from non-stationary data streams is a long-standing goal and a challenging problem in machine learning. Recently, we have witnessed a renewed and fast-growing interest in continual learning, especially within the deep learning community. However, algorithmic solutions are often difficult to re-implement, evaluate and port across different settings, where even results on standard benchmarks are hard to reproduce. In this work, we propose Avalanche, an open-source end-to-end library for continual learning research based on PyTorch. Avalanche is designed to provide a shared and collaborative codebase for fast prototyping, training, and reproducible evaluation of continual learning algorithms.

Cite

Text

Lomonaco et al. "Avalanche: An End-to-End Library for Continual Learning." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2021. doi:10.1109/CVPRW53098.2021.00399

Markdown

[Lomonaco et al. "Avalanche: An End-to-End Library for Continual Learning." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2021.](https://mlanthology.org/cvprw/2021/lomonaco2021cvprw-avalanche/) doi:10.1109/CVPRW53098.2021.00399

BibTeX

@inproceedings{lomonaco2021cvprw-avalanche,
  title     = {{Avalanche: An End-to-End Library for Continual Learning}},
  author    = {Lomonaco, Vincenzo and Pellegrini, Lorenzo and Cossu, Andrea and Carta, Antonio and Graffieti, Gabriele and Hayes, Tyler L. and De Lange, Matthias and Masana, Marc and Pomponi, Jary and van de Ven, Gido M. and Mundt, Martin and She, Qi and Cooper, Keiland W. and Forest, Jeremy and Belouadah, Eden and Calderara, Simone and Parisi, German Ignacio and Cuzzolin, Fabio and Tolias, Andreas S. and Scardapane, Simone and Antiga, Luca and Ahmad, Subutai and Popescu, Adrian and Kanan, Christopher and van de Weijer, Joost and Tuytelaars, Tinne and Bacciu, Davide and Maltoni, Davide},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2021},
  pages     = {3600-3610},
  doi       = {10.1109/CVPRW53098.2021.00399},
  url       = {https://mlanthology.org/cvprw/2021/lomonaco2021cvprw-avalanche/}
}