Continual Learning Achieves Reduced Forgetting Loss Via Joint Weight Optimisation
Scientists are tackling the persistent problem of ‘catastrophic forgetting’ in artificial intelligence, where machine learning models struggle to retain previously...
Continual
Building adaptive knowledge bases for evolving continual learning models
This section details a new method for adapter-based, task-free continual learning utilizing a policy optimization approach to decide tasks. First,...
Domain-incremental white blood cell classification with privacy-aware continual learning
DatasetsWe utilize a series of WBC datasets demonstrating challenging domain shifts commonly found in clinical settings, which we refer to...
RanDumb: A Simple Yet Powerful AI Approach to Exemplar-Free Continual Learning
Continual learning is a rapidly evolving area of research that focuses on developing models capable of learning from sequentially arriving...
