Jrn-Henrik Jacobsen
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
15
Venues
5
Active years
2016–2025
Best venue rank
A*
Where they publish
Papers
15 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICML | Addressing Misspecification in Simulation-based Inference through Data-driven Calibration. | Antoine Wehenkel, Juan L. Gamella, Ozan Sener, Jens Behrmann, Guillermo Sapiro, Jrn-Henrik Jacobsen, Marco Cuturi |
| 2021 | AISTATS | Understanding and Mitigating Exploding Inverses in Invertible Neural Networks. | Jens Behrmann, Paul Vicol, Kuan-Chieh Wang, Roger B. Grosse, Jrn-Henrik Jacobsen |
| 2021 | ICML | Environment Inference for Invariant Learning. | Elliot Creager, Jrn-Henrik Jacobsen, Richard S. Zemel |
| 2021 | ICML | Out-of-Distribution Generalization via Risk Extrapolation (REx). | David Krueger, Ethan Caballero, Jrn-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Rmi Le Priol, Aaron C. Courville |
| 2020 | ICLR | Understanding the Limitations of Conditional Generative Models. | Ethan Fetaya, Jrn-Henrik Jacobsen, Will Grathwohl, Richard S. Zemel |
| 2020 | ICLR | Your classifier is secretly an energy based model and you should treat it like one. | Will Grathwohl, Kuan-Chieh Wang, Jrn-Henrik Jacobsen, David Duvenaud, Mohammad Norouzi, Kevin Swersky |
| 2020 | ICML | How to Train Your Neural ODE: the World of Jacobian and Kinetic Regularization. | Chris Finlay, Jrn-Henrik Jacobsen, Levon Nurbekyan, Adam M. Oberman |
| 2020 | ICML | Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling. | Will Grathwohl, Kuan-Chieh Wang, Jrn-Henrik Jacobsen, David Duvenaud, Richard S. Zemel |
| 2020 | ICML | Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations. | Florian Tramr, Jens Behrmann, Nicholas Carlini, Nicolas Papernot, Jrn-Henrik Jacobsen |
| 2019 | ICLR | Excessive Invariance Causes Adversarial Vulnerability. | Jrn-Henrik Jacobsen, Jens Behrmann, Richard S. Zemel, Matthias Bethge |
| 2019 | ICML | Invertible Residual Networks. | Jens Behrmann, Will Grathwohl, Ricky T. Q. Chen, David Duvenaud, Jrn-Henrik Jacobsen |
| 2019 | ICML | Flexibly Fair Representation Learning by Disentanglement. | Elliot Creager, David Madras, Jrn-Henrik Jacobsen, Marissa A. Weis, Kevin Swersky, Toniann Pitassi, Richard S. Zemel |
| 2018 | ICLR | i-RevNet: Deep Invertible Networks. | Jrn-Henrik Jacobsen, Arnold W. M. Smeulders, Edouard Oyallon |
| 2017 | BMVC | Dynamic Steerable Blocks in Deep Residual Networks. | Jrn-Henrik Jacobsen, Bert De Brabandere, Arnold W. M. Smeulders |
| 2016 | CVPR | Structured Receptive Fields in CNNs. | Jrn-Henrik Jacobsen, Jan C. van Gemert, Zhongyu Lou, Arnold W. M. Smeulders |