Julian Bitterwolf

About Julian Bitterwolf

Julian Bitterwolf, With an exceptional h-index of 7 and a recent h-index of 7 (since 2020), a distinguished researcher at Eberhard Karls Universität Tübingen, specializes in the field of Computer Science, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation

Provably Adversarially Robust Detection of Out-of-distribution Data (almost) for free

Neural Network Heuristic Functions: Taking Confidence into Account

Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities

Classifiers should do well even on their worst classes

Revisiting out-of-distribution detection: A simple baseline is surprisingly effective

Provably Robust Detection of Out-of-distribution Data (almost) for free

Certifiably adversarially robust detection of out-of-distribution data

Julian Bitterwolf Information

University

Position

PhD Student

Citations(all)

849

Citations(since 2020)

847

Cited By

159

hIndex(all)

7

hIndex(since 2020)

7

i10Index(all)

7

i10Index(since 2020)

7

Email

University Profile Page

Eberhard Karls Universität Tübingen

Google Scholar

View Google Scholar Profile

Julian Bitterwolf Skills & Research Interests

Computer Science

Machine Learning

Top articles of Julian Bitterwolf

Title

Journal

Author(s)

Publication Date

In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation

arXiv preprint arXiv:2306.00826

Julian Bitterwolf

Maximilian Mueller

Matthias Hein

2023/6/1

Provably Adversarially Robust Detection of Out-of-distribution Data (almost) for free

Advances in Neural Information Processing Systems

Alexander Meinke

Julian Bitterwolf

Matthias Hein

2022/12/6

Neural Network Heuristic Functions: Taking Confidence into Account

Proceedings of the International Symposium on Combinatorial Search

Daniel Heller

Patrick Ferber

Julian Bitterwolf

Matthias Hein

Jörg Hoffmann

2022/7/17

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

Matthias Hein

2022/6/28

Classifiers should do well even on their worst classes

Julian Bitterwolf

Alexander Meinke

Valentyn Boreiko

Matthias Hein

2022/6/4

Revisiting out-of-distribution detection: A simple baseline is surprisingly effective

Julian Bitterwolf

Alexander Meinke

Maximilian Augustin

Matthias Hein

2021/10/6

Provably Robust Detection of Out-of-distribution Data (almost) for free

arXiv preprint arXiv:2106.04260

Alexander Meinke

Julian Bitterwolf

Matthias Hein

2021/6/8

Certifiably adversarially robust detection of out-of-distribution data

Advances in Neural Information Processing Systems

Julian Bitterwolf

Alexander Meinke

Matthias Hein

2020

A simple way to make neural networks robust against diverse image corruptions

Evgenia Rusak

Lukas Schott

Roland S Zimmermann

Julian Bitterwolf

Oliver Bringmann

...

2020

Increasing the robustness of dnns against im-age corruptions by playing the game of noise

Evgenia Rusak

Lukas Schott

Roland Zimmermann

Julian Bitterwolfb

Oliver Bringmann

...

2020

See List of Professors in Julian Bitterwolf University(Eberhard Karls Universität Tübingen)