Brain-Inspired Continual Learning-Robust Feature Distillation and Re-Consolidation for Class Incremental Learning

arXiv:2404.14588v1 Announce Type: new
Abstract: Artificial intelligence (AI) and neuroscience share a rich history, with advancements in neuroscience shaping the development of AI systems capable of human-like knowledge retention. Leveraging insights from neuroscience and existing research in adversarial and continual learning, we introduce a novel framework comprising two core concepts: feature distillation and re-consolidation. Our framework, named Robust Rehearsal, addresses the challenge of catastrophic forgetting inherent in continual learning (CL) systems by distilling and rehearsing robust features. Inspired by the …

abstract adversarial ai systems artificial artificial intelligence arxiv brain brain-inspired class consolidation continual core cs.cv cs.lg development distillation feature framework history human human-like incremental insights intelligence knowledge neuroscience novel research retention robust systems type