arXiv · 2111.13297
Latent Space based Memory Replay for Continual Learning in Artificial Neural Networks
Abstract
Memory replay may be key to learning in biological brains, which manage to learn new tasks continually without catastrophically interfering with previous knowledge. On the other hand, artificial neural networks suffer from catastrophic forgetting and tend to only perform well on tasks that they were recently trained on. In this work we explore the application of latent space based memory replay for classification using artificial neural networks. We are able to preserve good performance in previous tasks by storing only a small percentage of the original data in a compressed latent space version.
Explore related subjects
Keep this discovery
Haitz Sáez de Ocáriz Borde. 2021-11-26. Latent Space based Memory Replay for Continual Learning in Artificial Neural Networks. https://arxiv.org/abs/2111.13297
Cite the original work for its findings. Save a collection to share your selection of sources.