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Jörn-Henrik Jacobsen

Observed names: Jacobsen, Jorn-Henrik, Jacobsen, Jörn-Henrik, Jorn-Henrik Jacobsen
Observed institutions: Apple (Israel), University of Liège, University of Toronto, Vector Institute, Apple (United States), New York University, University of Amsterdam
OpenAlex ID: A5109463535
Shortcut learning in deep neural networks
2020 · Robert Geirhos, Jörn-Henrik Jacobsen, et al. · Nature Machine Intelligence · 2,168
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Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
2019 · Grathwohl, Will, Wang, Kuan-Chieh, et al. · arXiv (Cornell University) · 209
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Flexibly Fair Representation Learning by Disentanglement
2019 · Creager, Elliot, Madras, David, et al. · arXiv (Cornell University) · 186
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i-RevNet: Deep Invertible Networks
2018 · Jacobsen, Jörn-Henrik, Smeulders, Arnold, et al. · arXiv (Cornell University) · 173
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Invertible Residual Networks
2018 · Behrmann, Jens, Grathwohl, Will, et al. · arXiv (Cornell University) · 150
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How to train your neural ODE: the world of Jacobian and kinetic regularization
2020 · Finlay, Chris, Jacobsen, Jörn-Henrik, et al. · arXiv (Cornell University) · 120
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Excessive Invariance Causes Adversarial Vulnerability
2018 · Jacobsen, Jörn-Henrik, Behrmann, Jens, et al. · arXiv (Cornell University) · 77
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Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations
2020 · Tramèr, Florian, Behrmann, Jens, et al. · arXiv (Cornell University) · 52
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Understanding and Mitigating Exploding Inverses in Invertible Neural Networks
2020 · Behrmann, Jens, Vicol, Paul, et al. · arXiv (Cornell University) · 37
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Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling
2020 · Grathwohl, Will, Wang, Kuan-Chieh, et al. · arXiv (Cornell University) · 35
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Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness
2019 · Jacobsen, Jörn-Henrik, Behrmannn, Jens, et al. · arXiv (Cornell University) · 27
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Structured Receptive Fields in CNNs
2016 · Jorn-Henrik Jacobsen, Jan Van Gemert, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 20
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Dynamic Steerable Blocks in Deep Residual Networks
2017 · Jörn-Henrik Jacobsen, Bert De Brabandere, et al. · British Machine Vision Conference (BMVC) · 19
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Conditional Generative Models are not Robust
2019 · Ethan Fetaya, Jörn-Henrik Jacobsen, et al. · arXiv (Cornell University) · 11
Multiscale Hierarchical Convolutional Networks
2017 · Jacobsen, Jörn-Henrik, Oyallon, Edouard, et al. · arXiv (Cornell University) · 10
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Robust Hybrid Learning With Expert Augmentation
2022 · Wehenkel, Antoine, Behrmann, Jens, et al. · arXiv (Cornell University) · 6
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On the Invertibility of Invertible Neural Networks
2019 · Jens Behrmann, Paul Vicol, et al. · 6
Addressing Misspecification in Simulation-based Inference through Data-driven Calibration
2024 · Wehenkel, Antoine, Gamella, Juan L., et al. · arXiv (Cornell University) · 3
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Simulation-based Inference for Cardiovascular Models
2023 · Wehenkel, Antoine, Manduchi, Laura, et al. · arXiv (Cornell University) · 3
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Learning Invariant Representations with Missing Data
2021 · Goldstein, Mark, Jacobsen, Jörn-Henrik, et al. · PubMed · 2
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Inferring Optical Tissue Properties from Photoplethysmography using Hybrid Amortized Inference
2025 · Behrmann, Jens, Cervera, Maria R., et al. · arXiv (Cornell University) · 1
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Considerations for Distribution Shift Robustness of Diagnostic Models in Healthcare
2024 · Blaas, Arno, Goliński, Adam, et al. · arXiv (Cornell University) · 1
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Unintended cue learning: Lessons for deep learning from experimental psychology
2020 · Robert Geirhos, Jörn-Henrik Jacobsen, et al. · Journal of Vision · 1
Inferring optical tissue properties from photoplethysmography using hybrid amortized inference
2026 · Jens Behrmann, Maria R Cervera, et al. · Machine Learning Health
Author response for "Inferring Optical Tissue Properties from Photoplethysmography using Hybrid Amortized Inference"
2026 · Behrmann, Jens, Cervera, Maria R., et al.
Works count: 27
Citation count: 3,313
H-index: 13
I10-index: 15
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