41 citations · 88 across the 8 of their papers we have counts for
3 papers · 1 filter
Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities
Julian Bitterwolf, Alexander Meinke, Maximilian Augustin +1
It is an important problem in trustworthy machine learning to recognize out-of-distribution (OOD) inputs which are inputs unrelated to the in-distribution task. Many out-of-distrib…
Out-distribution aware Self-training in an Open World Setting
Maximilian Augustin, Matthias Hein
Deep Learning heavily depends on large labeled datasets which limits further improvements. While unlabeled data is available in large amounts, in particular in image recognition, i…
Adversarial Robustness on In- and Out-Distribution Improves Explainability
Maximilian Augustin, Alexander Meinke, Matthias Hein
Neural networks have led to major improvements in image classification but suffer from being non-robust to adversarial changes, unreliable uncertainty estimates on out-distribution…