305 citations · 534 across the 23 of their papers we have counts for
4 papers · 1 filter
Beyond Supervised Continual Learning: a Review
Benedikt Bagus, Alexander Gepperth, Timothée Lesort
Continual Learning (CL, sometimes also termed incremental learning) is a flavor of machine learning where the usual assumption of stationary data distribution is relaxed or omitted…
Continual Learning with Foundation Models: An Empirical Study of Latent Replay
Oleksiy Ostapenko, Timothee Lesort, Pau Rodríguez +4
Rapid development of large-scale pre-training has resulted in foundation models that can act as effective feature extractors on a variety of downstream tasks and domains. Motivated…
Challenging Common Assumptions about Catastrophic Forgetting
Timothée Lesort, Oleksiy Ostapenko, Diganta Misra +4
Building learning agents that can progressively learn and accumulate knowledge is the core goal of the continual learning (CL) research field. Unfortunately, training a model on ne…
Continual Feature Selection: Spurious Features in Continual Learning
Timothée Lesort
Continual Learning (CL) is the research field addressing learning without forgetting when the data distribution is not static. This paper studies spurious features' influence on co…