עקוב אחר
Jörn-Henrik Jacobsen
Jörn-Henrik Jacobsen
Apple AI/ML Research
כתובת אימייל מאומתת בדומיין vectorinstitute.ai - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
Shortcut learning in deep neural networks‏
R Geirhos, JH Jacobsen, C Michaelis, R Zemel, W Brendel, M Bethge, ...‏
Nature Machine Intelligence 2 (11), 665-673, 2020‏
20952020
Out-of-distribution generalization via risk extrapolation (rex)‏
D Krueger, E Caballero, JH Jacobsen, A Zhang, J Binas, D Zhang, ...‏
International conference on machine learning, 5815-5826, 2021‏
9312021
Invertible residual networks‏
J Behrmann, W Grathwohl, RTQ Chen, D Duvenaud, JH Jacobsen‏
International conference on machine learning, 573-582, 2019‏
7002019
Your classifier is secretly an energy based model and you should treat it like one‏
W Grathwohl, KC Wang, JH Jacobsen, D Duvenaud, M Norouzi, ...‏
arXiv preprint arXiv:1912.03263, 2019‏
6192019
Why musical memory can be preserved in advanced Alzheimer’s disease‏
JH Jacobsen, J Stelzer, TH Fritz, G Chételat, R La Joie, R Turner‏
Brain: a Journal of Neurology 138 (8), 2438-2450, 2015‏
4272015
Residual flows for invertible generative modeling‏
RTQ Chen, J Behrmann, DK Duvenaud, JH Jacobsen‏
Advances in Neural Information Processing Systems 32, 2019‏
4112019
Flexibly fair representation learning by disentanglement‏
E Creager, D Madras, JH Jacobsen, M Weis, K Swersky, T Pitassi, ...‏
International conference on machine learning, 1436-1445, 2019‏
4082019
i-RevNet: Deep Invertible Networks‏
JH Jacobsen, A Smeulders, E Oyallon‏
International Conference on Learning Representations (ICLR), 2018‏
4072018
Environment inference for invariant learning‏
E Creager, JH Jacobsen, R Zemel‏
International Conference on Machine Learning, 2189-2200, 2021‏
4012021
How to train your neural ODE: the world of Jacobian and kinetic regularization‏
C Finlay, JH Jacobsen, L Nurbekyan, A Oberman‏
International conference on machine learning, 3154-3164, 2020‏
317*2020
Excessive invariance causes adversarial vulnerability‏
JH Jacobsen, J Behrmann, R Zemel, M Bethge‏
arXiv preprint arXiv:1811.00401, 2018‏
1932018
Fundamental tradeoffs between invariance and sensitivity to adversarial perturbations‏
F Tramèr, J Behrmann, N Carlini, N Papernot, JH Jacobsen‏
International conference on machine learning, 9561-9571, 2020‏
141*2020
Structured Receptive Fields in CNNs‏
JH Jacobsen, J van Gemert, Z Lou, AWM Smeulders‏
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2610-2619, 2016‏
1312016
Understanding and mitigating exploding inverses in invertible neural networks‏
J Behrmann, P Vicol, KC Wang, R Grosse, JH Jacobsen‏
International Conference on Artificial Intelligence and Statistics, 1792-1800, 2021‏
1182021
Preventing gradient attenuation in lipschitz constrained convolutional networks‏
Q Li, S Haque, C Anil, J Lucas, RB Grosse, JH Jacobsen‏
Advances in neural information processing systems 32, 2019‏
1122019
Learning the stein discrepancy for training and evaluating energy-based models without sampling‏
W Grathwohl, KC Wang, JH Jacobsen, D Duvenaud, R Zemel‏
International Conference on Machine Learning, 3732-3747, 2020‏
962020
Understanding the Limitations of Conditional Generative Models‏
E Fetaya, JH Jacobsen, W Grathwohl, R Zemel‏
arXiv preprint arXiv:1906.01171, 2019‏
60*2019
Dynamic steerable blocks in deep residual networks‏
JH Jacobsen, B De Brabandere, AWM Smeulders‏
arXiv preprint arXiv:1706.00598, 2017‏
282017
Hierarchical Attribute CNNs‏
JH Jacobsen, E Oyallon, S Mallat, AWM Smeulders‏
ICML 2017 Workshop on Principled Approaches to Deep Learning, 2017‏
27*2017
Joint energy-based models for semi-supervised classification‏
S Zhao, JH Jacobsen, W Grathwohl‏
ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning 1, 2020‏
192020
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מאמרים 1–20