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Julian Bitterwolf
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2020 – today
- 2023
- [c8]Julian Bitterwolf, Maximilian Müller, Matthias Hein:
In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation. ICML 2023: 2471-2506 - [i6]Julian Bitterwolf, Maximilian Müller, Matthias Hein:
In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation. CoRR abs/2306.00826 (2023) - 2022
- [c7]Julian Bitterwolf, Alexander Meinke, Maximilian Augustin, Matthias Hein:
Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities. ICML 2022: 2041-2074 - [c6]Alexander Meinke, Julian Bitterwolf, Matthias Hein:
Provably Adversarially Robust Detection of Out-of-Distribution Data (Almost) for Free. NeurIPS 2022 - [c5]Daniel Heller, Patrick Ferber, Julian Bitterwolf, Matthias Hein, Jörg Hoffmann:
Neural Network Heuristic Functions: Taking Confidence into Account. SOCS 2022: 223-228 - [i5]Julian Bitterwolf, Alexander Meinke, Maximilian Augustin, Matthias Hein:
Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities. CoRR abs/2206.09880 (2022) - 2021
- [i4]Alexander Meinke, Julian Bitterwolf, Matthias Hein:
Provably Robust Detection of Out-of-distribution Data (almost) for free. CoRR abs/2106.04260 (2021) - 2020
- [c4]Evgenia Rusak, Lukas Schott, Roland S. Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel:
A Simple Way to Make Neural Networks Robust Against Diverse Image Corruptions. ECCV (3) 2020: 53-69 - [c3]Julian Bitterwolf, Alexander Meinke, Matthias Hein:
Certifiably Adversarially Robust Detection of Out-of-Distribution Data. NeurIPS 2020 - [i3]Evgenia Rusak, Lukas Schott, Roland S. Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel:
Increasing the robustness of DNNs against image corruptions by playing the Game of Noise. CoRR abs/2001.06057 (2020) - [i2]Julian Bitterwolf, Alexander Meinke, Matthias Hein:
Provable Worst Case Guarantees for the Detection of Out-of-Distribution Data. CoRR abs/2007.08473 (2020)
2010 – 2019
- 2019
- [c2]Matthias Hein, Maksym Andriushchenko, Julian Bitterwolf:
Why ReLU Networks Yield High-Confidence Predictions Far Away From the Training Data and How to Mitigate the Problem. CVPR 2019: 41-50 - [c1]Matthias Hein, Maksym Andriushchenko, Julian Bitterwolf:
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem. CVPR Workshops 2019: 58-74 - 2018
- [i1]Matthias Hein, Maksym Andriushchenko, Julian Bitterwolf:
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem. CoRR abs/1812.05720 (2018)
Coauthor Index
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