Jens Behrmann

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 20

Top Topics

Category Recognition

Mass Spectrometry

Invariant Properties

Top Venues

Publications

Antoine Wehenkel, Juan L. Gamella, Ozan Sener, Jens Behrmann, Guillermo Sapiro, Marco Cuturi, Jörn-Henrik Jacobsen
Addressing Misspecification in Simulation-based Inference through Data-driven Calibration. CoRR (2024)
Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, Gilles Louppe, Jörn-Henrik Jacobsen
Robust Hybrid Learning With Expert Augmentation. Trans. Mach. Learn. Res. 2023 (2023)
Antoine Wehenkel, Jens Behrmann, Andrew C. Miller, Guillermo Sapiro, Ozan Sener, Marco Cuturi, Jörn-Henrik Jacobsen
Simulation-based Inference for Cardiovascular Models. CoRR (2023)
Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, Gilles Louppe, Jörn-Henrik Jacobsen
Robust Hybrid Learning With Expert Augmentation. CoRR (2022)
Niklas Koenen, Marvin N. Wright, Peter Maaß, Jens Behrmann
Generalization of the Change of Variables Formula with Applications to Residual Flows. CoRR (2021)
Jens Behrmann, Paul Vicol, Kuan-Chieh Wang, Roger B. Grosse, Jörn-Henrik Jacobsen
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks. AISTATS (2021)
Florian Tramèr, Jens Behrmann, Nicholas Carlini, Nicolas Papernot, Jörn-Henrik Jacobsen
Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations. ICML (2020)
Jens Behrmann, Paul Vicol, Kuan-Chieh Wang, Roger B. Grosse, Jörn-Henrik Jacobsen
Understanding and mitigating exploding inverses in invertible neural networks. CoRR (2020)
Florian Tramèr, Jens Behrmann, Nicholas Carlini, Nicolas Papernot, Jörn-Henrik Jacobsen
Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations. CoRR (2020)
Christian Etmann, Maximilian Schmidt, Jens Behrmann, Tobias Boskamp, Lena Hauberg-Lotte, Annette Peter, Rita Casadonte, Jörg Kriegsmann, Peter Maass
Deep Relevance Regularization: Interpretable and Robust Tumor Typing of Imaging Mass Spectrometry Data. CoRR (2019)
Jens Behrmann, Will Grathwohl, Ricky T. Q. Chen, David Duvenaud, Jörn-Henrik Jacobsen
Invertible Residual Networks. ICML (2019)
Jörn-Henrik Jacobsen, Jens Behrmann, Richard S. Zemel, Matthias Bethge
Excessive Invariance Causes Adversarial Vulnerability. ICLR (Poster) (2019)
Tian Qi Chen, Jens Behrmann, David Duvenaud, Jörn-Henrik Jacobsen
Residual Flows for Invertible Generative Modeling. NeurIPS (2019)
Ricky T. Q. Chen, Jens Behrmann, David Duvenaud, Jörn-Henrik Jacobsen
Residual Flows for Invertible Generative Modeling. CoRR (2019)
Jörn-Henrik Jacobsen, Jens Behrmann, Nicholas Carlini, Florian Tramèr, Nicolas Papernot
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness. CoRR (2019)
Jens Behrmann, Christian Etmann, Tobias Boskamp, Rita Casadonte, Jörg Kriegsmann, Peter Maaß
Deep learning for tumor classification in imaging mass spectrometry. Bioinform. 34 (7) (2018)
Jörn-Henrik Jacobsen, Jens Behrmann, Richard S. Zemel, Matthias Bethge
Excessive Invariance Causes Adversarial Vulnerability. CoRR (2018)
Jens Behrmann, David Duvenaud, Jörn-Henrik Jacobsen
Invertible Residual Networks. CoRR (2018)
Jens Behrmann, Sören Dittmer, Pascal Fernsel, Peter Maaß
Analysis of Invariance and Robustness via Invertibility of ReLU-Networks. CoRR (2018)
Jens Behrmann, Christian Etmann, Tobias Boskamp, Rita Casadonte, Jörg Kriegsmann, Peter Maass
Deep Learning for Tumor Classification in Imaging Mass Spectrometry. CoRR (2017)