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Kevin Roth
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2020 – today
- 2021
- [b1]Kevin Roth:
Robustness and Regularization of Deep Neural Networks. ETH Zurich, Zürich, Switzerland, 2021 - [c8]Lorenzo Noci, Kevin Roth, Gregor Bachmann, Sebastian Nowozin, Thomas Hofmann:
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect. NeurIPS 2021: 12738-12748 - [c7]Lorenzo Noci, Gregor Bachmann, Kevin Roth, Sebastian Nowozin, Thomas Hofmann:
Precise characterization of the prior predictive distribution of deep ReLU networks. NeurIPS 2021: 20851-20862 - [i10]Kevin Roth:
A Primer on Multi-Neuron Relaxation-based Adversarial Robustness Certification. CoRR abs/2106.03099 (2021) - [i9]Lorenzo Noci, Kevin Roth, Gregor Bachmann, Sebastian Nowozin, Thomas Hofmann:
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect. CoRR abs/2106.06596 (2021) - [i8]Lorenzo Noci, Gregor Bachmann, Kevin Roth, Sebastian Nowozin, Thomas Hofmann:
Precise characterization of the prior predictive distribution of deep ReLU networks. CoRR abs/2106.06615 (2021) - 2020
- [c6]Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin:
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. ICML 2020: 9289-9299 - [c5]Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin:
How Good is the Bayes Posterior in Deep Neural Networks Really? ICML 2020: 10248-10259 - [c4]Kevin Roth, Yannic Kilcher, Thomas Hofmann:
Adversarial Training is a Form of Data-dependent Operator Norm Regularization. NeurIPS 2020 - [i7]Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton:
Hydra: Preserving Ensemble Diversity for Model Distillation. CoRR abs/2001.04694 (2020) - [i6]Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin:
How Good is the Bayes Posterior in Deep Neural Networks Really? CoRR abs/2002.02405 (2020) - [i5]Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin:
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. CoRR abs/2002.02655 (2020)
2010 – 2019
- 2019
- [c3]Kevin Roth, Yannic Kilcher, Thomas Hofmann:
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples. ICML 2019: 5498-5507 - [i4]Kevin Roth, Yannic Kilcher, Thomas Hofmann:
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples. CoRR abs/1902.04818 (2019) - [i3]Kevin Roth, Yannic Kilcher, Thomas Hofmann:
Adversarial Training Generalizes Data-dependent Spectral Norm Regularization. CoRR abs/1906.01527 (2019) - 2018
- [c2]Didier Keymeulen, Simon Shin, Jason Riddley, Matthew Klimesh, Aaron B. Kiely, Elliott Liggett, Peter Sullivan, Michael Bernas, Hamid Ghossemi, Greg Flesch, Michael Cheng, Sam Dolinar, David Dolman, Kevin Roth, Chris Holyoake, Ken Crocker, Adam Smith:
High Performance Space Computing with System-on-Chip Instrument Avionics for Space-based Next Generation Imaging Spectrometers (NGIS). AHS 2018: 33-36 - [i2]Kevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann:
Adversarially Robust Training through Structured Gradient Regularization. CoRR abs/1805.08736 (2018) - 2017
- [c1]Kevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann:
Stabilizing Training of Generative Adversarial Networks through Regularization. NIPS 2017: 2018-2028 - [i1]Kevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann:
Stabilizing Training of Generative Adversarial Networks through Regularization. CoRR abs/1705.09367 (2017)
Coauthor Index
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