A comprehensive, application-oriented study of catastrophic forgetting in DNNs

ICLR 2019 B. PfülbA. Gepperth

We present a large-scale empirical study of catastrophic forgetting (CF) in modern Deep Neural Network (DNN) models that perform sequential (or: incremental) learning. A new experimental protocol is proposed that enforces typical constraints encountered in application scenarios... (read more)

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