Sven Gowal

According to our database, Sven Gowal authored at least 55 papers between 2009 and 2024.

Collaborative distances:

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

2024

Evaluating Model Bias Requires Characterizing its Mistakes.

Isabela Albuquerque, Jessica Schrouff, David Warde-Farley, Ali Taylan Cemgil, Sven Gowal, Olivia Wiles

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Generative models improve fairness of medical classifiers under distribution shifts.

Ira Ktena, Olivia Wiles, Isabela Albuquerque, Sylvestre-Alvise Rebuffi, Ryutaro Tanno, Abhijit Guha Roy, Shekoofeh Azizi, Danielle Belgrave, Pushmeet Kohli, Alan Karthikesalingam, A. Taylan Cemgil, Sven Gowal

CoRR, 2023

Differentially Private Diffusion Models Generate Useful Synthetic Images.

Sahra Ghalebikesabi, Leonard Berrada, Sven Gowal, Ira Ktena, Robert Stanforth, Jamie Hayes, Soham De, Samuel L. Smith, Olivia Wiles, Borja Balle

CoRR, 2023

Benchmarking Robustness to Adversarial Image Obfuscations.

Florian Stimberg, Ayan Chakrabarti, Chun-Ta Lu, Hussein Hazimeh, Otilia Stretcu, Wei Qiao, Yintao Liu, Merve Kaya, Cyrus Rashtchian, Ariel Fuxman, Mehmet Tek, Sven Gowal

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Revisiting adapters with adversarial training.

Sylvestre-Alvise Rebuffi, Francesco Croce, Sven Gowal

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Seasoning Model Soups for Robustness to Adversarial and Natural Distribution Shifts.

Francesco Croce, Sylvestre-Alvise Rebuffi, Evan Shelhamer, Sven Gowal

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Discovering Bugs in Vision Models using Off-the-shelf Image Generation and Captioning.

Olivia Wiles, Isabela Albuquerque, Sven Gowal

CoRR, 2022

Robustness of Epinets against Distributional Shifts.

Xiuyuan Lu, Ian Osband, Seyed Mohammad Asghari, Sven Gowal, Vikranth Dwaracherla, Zheng Wen, Benjamin Van Roy

CoRR, 2022

Competition-Level Code Generation with AlphaCode.

Yujia Li, David H. Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d'Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J. Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, Oriol Vinyals

CoRR, 2022

Hindering Adversarial Attacks with Implicit Neural Representations.

Andrei A. Rusu, Dan Andrei Calian, Sven Gowal, Raia Hadsell

Proceedings of the International Conference on Machine Learning, 2022

Evaluating the Adversarial Robustness of Adaptive Test-time Defenses.

Francesco Croce, Sven Gowal, Thomas Brunner, Evan Shelhamer, Matthias Hein, A. Taylan Cemgil

Proceedings of the International Conference on Machine Learning, 2022

A Fine-Grained Analysis on Distribution Shift.

Olivia Wiles, Sven Gowal, Florian Stimberg, Sylvestre-Alvise Rebuffi, Ira Ktena, Krishnamurthy Dvijotham, Ali Taylan Cemgil

Proceedings of the Tenth International Conference on Learning Representations, 2022

Defending Against Image Corruptions Through Adversarial Augmentations.

Dan Andrei Calian, Florian Stimberg, Olivia Wiles, Sylvestre-Alvise Rebuffi, András György, Timothy A. Mann, Sven Gowal

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Challenges of real-world reinforcement learning: definitions, benchmarks and analysis.

Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester

Mach. Learn., 2021

An Empirical Investigation of Learning from Biased Toxicity Labels.

Neel Nanda, Jonathan Uesato, Sven Gowal

CoRR, 2021

A Closer Look at the Adversarial Robustness of Information Bottleneck Models.

Iryna Korshunova, David Stutz, Alexander A. Alemi, Olivia Wiles, Sven Gowal

CoRR, 2021

Fixing Data Augmentation to Improve Adversarial Robustness.

Sylvestre-Alvise Rebuffi, Sven Gowal, Dan A. Calian, Florian Stimberg, Olivia Wiles, Timothy A. Mann

CoRR, 2021

Verifying Probabilistic Specifications with Functional Lagrangians.

Leonard Berrada, Sumanth Dathathri, Krishnamurthy Dvijotham, Robert Stanforth, Rudy Bunel, Jonathan Uesato, Sven Gowal, M. Pawan Kumar

CoRR, 2021

Data Augmentation Can Improve Robustness.

Sylvestre-Alvise Rebuffi, Sven Gowal, Dan Andrei Calian, Florian Stimberg, Olivia Wiles, Timothy A. Mann

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

Improving Robustness using Generated Data.

Sven Gowal, Sylvestre-Alvise Rebuffi, Olivia Wiles, Florian Stimberg, Dan Andrei Calian, Timothy A. Mann

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

Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications.

Leonard Berrada, Sumanth Dathathri, Krishnamurthy Dvijotham, Robert Stanforth, Rudy Bunel, Jonathan Uesato, Sven Gowal, M. Pawan Kumar

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

Self-supervised Adversarial Robustness for the Low-label, High-data Regime.

Sven Gowal, Po-Sen Huang, Aäron van den Oord, Timothy A. Mann, Pushmeet Kohli

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples.

Sven Gowal, Chongli Qin, Jonathan Uesato, Timothy A. Mann, Pushmeet Kohli

CoRR, 2020

An empirical investigation of the challenges of real-world reinforcement learning.

Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester

CoRR, 2020

The Autoencoding Variational Autoencoder.

A. Taylan Cemgil, Sumedh Ghaisas, Krishnamurthy Dvijotham, Sven Gowal, Pushmeet Kohli

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

Towards Stable and Efficient Training of Verifiably Robust Neural Networks.

Huan Zhang, Hongge Chen, Chaowei Xiao, Sven Gowal, Robert Stanforth, Bo Li, Duane S. Boning, Cho-Jui Hsieh

Proceedings of the 8th International Conference on Learning Representations, 2020

Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control.

Tsui-Wei Weng, Krishnamurthy (Dj) Dvijotham, Jonathan Uesato, Kai Xiao, Sven Gowal, Robert Stanforth, Pushmeet Kohli

Proceedings of the 8th International Conference on Learning Representations, 2020

Towards Verified Robustness under Text Deletion Interventions.

Johannes Welbl, Po-Sen Huang, Robert Stanforth, Sven Gowal, Krishnamurthy (Dj) Dvijotham, Martin Szummer, Pushmeet Kohli

Proceedings of the 8th International Conference on Learning Representations, 2020

A Framework for robustness Certification of Smoothed Classifiers using F-Divergences.

Krishnamurthy (Dj) Dvijotham, Jamie Hayes, Borja Balle, J. Zico Kolter, Chongli Qin, András György, Kai Xiao, Sven Gowal, Pushmeet Kohli

Proceedings of the 8th International Conference on Learning Representations, 2020

Towards Robust Image Classification Using Sequential Attention Models.

Daniel Zoran, Mike Chrzanowski, Po-Sen Huang, Sven Gowal, Alex Mott, Pushmeet Kohli

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Achieving Robustness in the Wild via Adversarial Mixing With Disentangled Representations.

Sven Gowal, Chongli Qin, Po-Sen Huang, A. Taylan Cemgil, Krishnamurthy Dvijotham, Timothy A. Mann, Pushmeet Kohli

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

An Alternative Surrogate Loss for PGD-based Adversarial Testing.

Sven Gowal, Jonathan Uesato, Chongli Qin, Po-Sen Huang, Timothy A. Mann, Pushmeet Kohli

CoRR, 2019

Efficient Neural Network Verification with Exactness Characterization.

Krishnamurthy (Dj) Dvijotham, Robert Stanforth, Sven Gowal, Chongli Qin, Soham De, Pushmeet Kohli

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Adversarial Robustness through Local Linearization.

Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Dual Approach to Verify and Train Deep Networks.

Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth, Timothy A. Mann, Pushmeet Kohli

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems.

Timothy A. Mann, Sven Gowal, András György, Huiyi Hu, Ray Jiang, Balaji Lakshminarayanan, Prav Srinivasan

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

Verification of Non-Linear Specifications for Neural Networks.

Chongli Qin, Krishnamurthy (Dj) Dvijotham, Brendan O'Donoghue, Rudy Bunel, Robert Stanforth, Sven Gowal, Jonathan Uesato, Grzegorz Swirszcz, Pushmeet Kohli

Proceedings of the 7th International Conference on Learning Representations, 2019

Beyond Greedy Ranking: Slate Optimization via List-CVAE.

Ray Jiang, Sven Gowal, Yuqiu Qian, Timothy A. Mann, Danilo J. Rezende

Proceedings of the 7th International Conference on Learning Representations, 2019

Scalable Verified Training for Provably Robust Image Classification.

Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth, Rudy Bunel, Chongli Qin, Jonathan Uesato, Relja Arandjelovic, Timothy Arthur Mann, Pushmeet Kohli

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation.

Po-Sen Huang, Robert Stanforth, Johannes Welbl, Chris Dyer, Dani Yogatama, Sven Gowal, Krishnamurthy Dvijotham, Pushmeet Kohli

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018

On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models.

Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth, Rudy Bunel, Chongli Qin, Jonathan Uesato, Relja Arandjelovic, Timothy A. Mann, Pushmeet Kohli

CoRR, 2018

Learning from Delayed Outcomes with Intermediate Observations.

Timothy A. Mann, Sven Gowal, Ray Jiang, Huiyi Hu, Balaji Lakshminarayanan, András György

CoRR, 2018

Training verified learners with learned verifiers.

Krishnamurthy Dvijotham, Sven Gowal, Robert Stanforth, Relja Arandjelovic, Brendan O'Donoghue, Jonathan Uesato, Pushmeet Kohli

CoRR, 2018

Optimizing Slate Recommendations via Slate-CVAE.

Ray Jiang, Sven Gowal, Timothy A. Mann, Danilo J. Rezende

CoRR, 2018

A Dual Approach to Scalable Verification of Deep Networks.

Krishnamurthy Dvijotham, Robert Stanforth, Sven Gowal, Timothy A. Mann, Pushmeet Kohli

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

2013

A Framework for Graph-Based Distributed Rendezvous of Nonholonomic Multi-Robot Systems.

Sven Gowal

PhD thesis, 2013

2012

A new collision warning system for lead vehicles in rear-end collisions.

Adrian Cabrera, Sven Gowal, Alcherio Martinoli

Proceedings of the 2012 IEEE Intelligent Vehicles Symposium, 2012

Real-Time Optimized Rendezvous on Nonholonomic Resource-Constrained Robots.

Sven Gowal, Alcherio Martinoli

Proceedings of the Experimental Robotics, 2012

Real-time optimization of trajectories that guarantee the rendezvous of mobile robots.

Sven Gowal, Alcherio Martinoli

Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012

2011

Two-phase online calibration for infrared-based inter-robot positioning modules.

Sven Gowal, Amanda Prorok, Alcherio Martinoli

Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011

Bayesian rendezvous for distributed robotic systems.

Sven Gowal, Alcherio Martinoli

Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011

2010

A realistic simulator for the design and evaluation of intelligent vehicles.

Sven Gowal, Yizhen Zhang, Alcherio Martinoli

Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems, 2010

Local graph-based distributed control for safe highway platooning.

Sven Gowal, Riccardo Falconi, Alcherio Martinoli

Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010

Graph based distributed control of non-holonomic vehicles endowed with local positioning information engaged in escorting missions.

Riccardo Falconi, Sven Gowal, Alcherio Martinoli

Proceedings of the IEEE International Conference on Robotics and Automation, 2010

2009

Graph-based distributed control for non-holonomic vehicles engaged in a reconfiguration task using local positioning information.

Riccardo Falconi, Sven Gowal, Jim Pugh, Alcherio Martinoli

Proceedings of the 2nd International ICST Conference on Robot Communication and Coordination, 2009