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Adiabatic replay for continual learning
In this proof-of-concept study, we propose a replay-based CL strategy that we term adiabatic replay (AR), which derives its efficiency from the (reasonable) assumption that each new learning phase is adiabatic, i. e., represents only a small addition to existing knowledge.
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