38 citations · 56 across the 2 of their papers we have counts for
2 papers
cs.LG2020★ 18 cited
A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning
Martin Mundt, Yongwon Hong, Iuliia Pliushch +1
Current deep learning methods are regarded as favorable if they empirically perform well on dedicated test sets. This mentality is seamlessly reflected in the resurfacing area of c…
cs.LG2019★ 38 cited
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition
Martin Mundt, Iuliia Pliushch, Sagnik Majumder +2
Modern deep neural networks are well known to be brittle in the face of unknown data instances and recognition of the latter remains a challenge. Although it is inevitable for cont…