38 citations · 122 across the 18 of their papers we have counts for
3 papers · 1 filter
Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?
Martin Mundt, Iuliia Pliushch, Sagnik Majumder +1
We present an analysis of predictive uncertainty based out-of-distribution detection for different approaches to estimate various models' epistemic uncertainty and contrast it with…
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…
Rethinking Layer-wise Feature Amounts in Convolutional Neural Network Architectures
Martin Mundt, Sagnik Majumder, Tobias Weis +1
We characterize convolutional neural networks with respect to the relative amount of features per layer. Using a skew normal distribution as a parametrized framework, we investigat…