Continual Learning with Deep Architectures

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Continual Reinforcement Learning in 3D Non-stationary Environments (2019, background): “tain past knowledge and skills in previously encountered environmental conditions or tasks [31, 41, 13, 24].”
Rehearsal-Free Continual Learning over Small Non-I.I.D. Batches (2019, positive): “on regularization, architectural or rehearsal approaches [24, 17, 2].”
Avalanche: an End-to-End Library for Continual Learning (2021, background): “In the last few years, machine learning has witnessed a prolific, variegated, and original research production on the topic: from Computer Vision [9, 31, 37]”
CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions (2020, background): “AI also known as Incremental or Lifelong Learning, has received a renewed attention from the research community over the last few years (Parisi et al., 2019; Lomonaco, 2019; Lesort et al., 2020).”
Fine-Grained Continual Learning (2019, background): “In recent years, a number of continual learning (CL) strategies have been proposed for deep architectures based on regularization , architectural or rehearsal approaches [8, 9].”