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Beyond Supervised Continual Learning: a Review
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.
A Study of Continual Learning Methods for Q-Learning
We present an empirical study on the use of continual learning (CL) methods in a reinforcement learning (RL) scenario, which, to the best of our knowledge, has not been described before.
An Investigation of Replay-based Approaches for Continual Learning
We find that the impact of sample selection increases when a smaller number of samples is stored.
Continual Learning with Fully Probabilistic Models
As a concrete realization of generative continual learning, we propose Gaussian Mixture Replay (GMR).
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