B. Pfülb

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

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 takes into account typical constraints encountered in application scenarios. As the inv…