Kevin Roth

According to our database, Kevin Roth authored at least 13 papers between 2017 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Robustness and Regularization of Deep Neural Networks.

Kevin Roth

PhD thesis, 2021

A Primer on Multi-Neuron Relaxation-based Adversarial Robustness Certification.

Kevin Roth

CoRR, 2021

Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect.

Lorenzo Noci, Kevin Roth, Gregor Bachmann, Sebastian Nowozin, Thomas Hofmann

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Precise characterization of the prior predictive distribution of deep ReLU networks.

Lorenzo Noci, Gregor Bachmann, Kevin Roth, Sebastian Nowozin, Thomas Hofmann

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Hydra: Preserving Ensemble Diversity for Model Distillation.

Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton

CoRR, 2020

Adversarial Training is a Form of Data-dependent Operator Norm Regularization.

Kevin Roth, Yannic Kilcher, Thomas Hofmann

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

How Good is the Bayes Posterior in Deep Neural Networks Really?

Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin

Proceedings of the 37th International Conference on Machine Learning, 2020

The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks.

Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Adversarial Training Generalizes Data-dependent Spectral Norm Regularization.

Kevin Roth, Yannic Kilcher, Thomas Hofmann

CoRR, 2019

The Odds are Odd: A Statistical Test for Detecting Adversarial Examples.

Kevin Roth, Yannic Kilcher, Thomas Hofmann

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Adversarially Robust Training through Structured Gradient Regularization.

Kevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann

CoRR, 2018

High Performance Space Computing with System-on-Chip Instrument Avionics for Space-based Next Generation Imaging Spectrometers (NGIS).

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

Proceedings of the 2018 NASA/ESA Conference on Adaptive Hardware and Systems, 2018

2017

Stabilizing Training of Generative Adversarial Networks through Regularization.

Kevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017