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 (ROBOCOMM, 2009)

Graph based distributed control of non-holonomic vehicles endowed with local positioning information engaged in escorting missions. - Riccardo Falconi; Sven Gowal; Alcherio Martinoli (ICRA, 2010)

Local graph-based distributed control for safe highway platooning. - Sven Gowal; Riccardo Falconi; Alcherio Martinoli (IROS, 2010)

A realistic simulator for the design and evaluation of intelligent vehicles. - Sven Gowal; Yizhen Zhang 002; Alcherio Martinoli (ITSC, 2010)

Bayesian rendezvous for distributed robotic systems. - Sven Gowal; Alcherio Martinoli (IROS, 2011)

Two-phase online calibration for infrared-based inter-robot positioning modules. - Sven Gowal; Amanda Prorok; Alcherio Martinoli (IROS, 2011)

Real-time optimization of trajectories that guarantee the rendezvous of mobile robots. - Sven Gowal; Alcherio Martinoli (IROS, 2012)

Real-Time Optimized Rendezvous on Nonholonomic Resource-Constrained Robots. - Sven Gowal; Alcherio Martinoli (ISER, 2012)

A new collision warning system for lead vehicles in rear-end collisions. - Adrian Cabrera; Sven Gowal; Alcherio Martinoli (Intelligent Vehicles Symposium, 2012)

A Framework for Graph-Based Distributed Rendezvous of Nonholonomic Multi-Robot Systems. - Sven Gowal (2013)

A Dual Approach to Scalable Verification of Deep Networks. - Krishnamurthy Dvijotham; Robert Stanforth; Sven Gowal; Timothy A. Mann; Pushmeet Kohli (UAI, 2018)

Optimizing Slate Recommendations via Slate-CVAE. - Ray Jiang; Sven Gowal; Timothy A. Mann; Danilo J. Rezende (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)

Learning from Delayed Outcomes with Intermediate Observations. - Timothy A. Mann; Sven Gowal; Ray Jiang; Huiyi Hu; Balaji Lakshminarayanan; András György 001 (CoRR, 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)

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 (EMNLP/IJCNLP (1), 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 (ICCV, 2019)

Beyond Greedy Ranking: Slate Optimization via List-CVAE. - Ray Jiang; Sven Gowal; Yuqiu Qian; Timothy A. Mann; Danilo J. Rezende (ICLR (Poster), 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 (ICLR (Poster), 2019)

Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems. - Timothy A. Mann; Sven Gowal; András György 001; Huiyi Hu; Ray Jiang; Balaji Lakshminarayanan; Prav Srinivasan (ICML, 2019)

A Dual Approach to Verify and Train Deep Networks. - Sven Gowal; Krishnamurthy Dvijotham; Robert Stanforth; Timothy A. Mann; Pushmeet Kohli (IJCAI, 2019)

Adversarial Robustness through Local Linearization. - Chongli Qin; James Martens; Sven Gowal; Dilip Krishnan; Krishnamurthy Dvijotham; Alhussein Fawzi; Soham De; Robert Stanforth; Pushmeet Kohli (NeurIPS, 2019)

Efficient Neural Network Verification with Exactness Characterization. - Krishnamurthy (Dj) Dvijotham; Robert Stanforth; Sven Gowal; Chongli Qin; Soham De; Pushmeet Kohli (UAI, 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)

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 (CVPR, 2020)

Towards Robust Image Classification Using Sequential Attention Models. - Daniel Zoran; Mike Chrzanowski; Po-Sen Huang; Sven Gowal; Alex Mott; Pushmeet Kohli (CVPR, 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 001; Kai Xiao; Sven Gowal; Pushmeet Kohli (ICLR, 2020)

Towards Verified Robustness under Text Deletion Interventions. - Johannes Welbl; Po-Sen Huang; Robert Stanforth; Sven Gowal; Krishnamurthy (Dj) Dvijotham; Martin Szummer; Pushmeet Kohli (ICLR, 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 (ICLR, 2020)

Towards Stable and Efficient Training of Verifiably Robust Neural Networks. - Huan Zhang 001; Hongge Chen; Chaowei Xiao; Sven Gowal; Robert Stanforth; Bo Li 026; Duane S. Boning; Cho-Jui Hsieh (ICLR, 2020)

The Autoencoding Variational Autoencoder. - A. Taylan Cemgil; Sumedh Ghaisas; Krishnamurthy Dvijotham; Sven Gowal; Pushmeet Kohli (NeurIPS, 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)

Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples. - Sven Gowal; Chongli Qin; Jonathan Uesato; Timothy A. Mann; Pushmeet Kohli (CoRR, 2020)

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 (ICLR, 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 (NeurIPS, 2021)

Improving Robustness using Generated Data. - Sven Gowal; Sylvestre-Alvise Rebuffi; Olivia Wiles; Florian Stimberg; Dan Andrei Calian; Timothy A. Mann (NeurIPS, 2021)

Data Augmentation Can Improve Robustness. - Sylvestre-Alvise Rebuffi; Sven Gowal; Dan Andrei Calian; Florian Stimberg; Olivia Wiles; Timothy A. Mann (NeurIPS, 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)

Fixing Data Augmentation to Improve Adversarial Robustness. - Sylvestre-Alvise Rebuffi; Sven Gowal; Dan A. Calian; Florian Stimberg; Olivia Wiles; Timothy A. Mann (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)

An Empirical Investigation of Learning from Biased Toxicity Labels. - Neel Nanda; Jonathan Uesato; Sven Gowal (CoRR, 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)

Defending Against Image Corruptions Through Adversarial Augmentations. - Dan Andrei Calian; Florian Stimberg; Olivia Wiles; Sylvestre-Alvise Rebuffi; András György 001; Timothy A. Mann; Sven Gowal (ICLR, 2022)

A Fine-Grained Analysis on Distribution Shift. - Olivia Wiles; Sven Gowal; Florian Stimberg; Sylvestre-Alvise Rebuffi; Ira Ktena; Krishnamurthy Dvijotham; Ali Taylan Cemgil (ICLR, 2022)

Evaluating the Adversarial Robustness of Adaptive Test-time Defenses. - Francesco Croce; Sven Gowal; Thomas Brunner; Evan Shelhamer; Matthias Hein 001; A. Taylan Cemgil (ICML, 2022)

Hindering Adversarial Attacks with Implicit Neural Representations. - Andrei A. Rusu; Dan Andrei Calian; Sven Gowal; Raia Hadsell (ICML, 2022)

Competition-Level Code Generation with AlphaCode. - Yujia Li 001; David H. Choi; Junyoung Chung; Nate Kushman; Julian Schrittwieser; Rémi Leblond; Tom Eccles; James Keeling; Felix Gimeno; Agustin Dal Lago; Thomas Hubert; Peter Choy; et al. (CoRR, 2022)

Robustness of Epinets against Distributional Shifts. - Xiuyuan Lu; Ian Osband; Seyed Mohammad Asghari; Sven Gowal; Vikranth Dwaracherla; Zheng Wen 002; Benjamin Van Roy (CoRR, 2022)

Discovering Bugs in Vision Models using Off-the-shelf Image Generation and Captioning. - Olivia Wiles; Isabela Albuquerque; Sven Gowal (CoRR, 2022)

Seasoning Model Soups for Robustness to Adversarial and Natural Distribution Shifts. - Francesco Croce; Sylvestre-Alvise Rebuffi; Evan Shelhamer; Sven Gowal (CVPR, 2023)

Revisiting adapters with adversarial training. - Sylvestre-Alvise Rebuffi; Francesco Croce; Sven Gowal (ICLR, 2023)

Benchmarking Robustness to Adversarial Image Obfuscations. - Florian Stimberg; Ayan Chakrabarti; Chun-Ta Lu; Hussein Hazimeh 001; Otilia Stretcu; Wei Qiao; Yintao Liu; Merve Kaya; Cyrus Rashtchian; Ariel Fuxman; Mehmet Tek; Sven Gowal (NeurIPS, 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)

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)

Evaluating Model Bias Requires Characterizing its Mistakes. - Isabela Albuquerque; Jessica Schrouff; David Warde-Farley; Ali Taylan Cemgil; Sven Gowal; Olivia Wiles (ICML, 2024)

Scalable watermarking for identifying large language model outputs. - Sumanth Dathathri; Abigail See; Sumedh Ghaisas; Po-Sen Huang; Rob McAdam; Johannes Welbl; Vandana Bachani; Alex Kaskasoli; Robert Stanforth; Tatiana Matejovicova; Jamie Hayes; Nidhi Vyas; et al. (Nat., 2024)

On the Difficulty of Constructing a Robust and Publicly-Detectable Watermark. - Jaiden Fairoze; Guillermo Ortiz-Jiménez; Mel Vecerík; Somesh Jha; Sven Gowal (AISTATS, 2025)