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

Training verified learners with learned verifiers. - Krishnamurthy Dvijotham; Sven Gowal; Robert Stanforth; Relja Arandjelovic; Brendan O'Donoghue; Jonathan Uesato; Pushmeet Kohli (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)

Strength in Numbers: Trading-off Robustness and Computation via Adversarially-Trained Ensembles. - Edward Grefenstette; Robert Stanforth; Brendan O'Donoghue; Jonathan Uesato; Grzegorz Swirszcz; 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)

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)

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

Are Labels Required for Improving Adversarial Robustness? - Jean-Baptiste Alayrac; Jonathan Uesato; Po-Sen Huang; Alhussein Fawzi; Robert Stanforth; Pushmeet Kohli (NeurIPS, 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)

Reducing Sentiment Bias in Language Models via Counterfactual Evaluation. - Po-Sen Huang; Huan Zhang; Ray Jiang; Robert Stanforth; Johannes Welbl; Jack Rae; Vishal Maini; Dani Yogatama; Pushmeet Kohli (EMNLP (Findings), 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)

Contrastive Training for Improved Out-of-Distribution Detection. - Jim Winkens; Rudy Bunel; Abhijit Guha Roy; Robert Stanforth; Vivek Natarajan; Joseph R. Ledsam; Patricia MacWilliams; Pushmeet Kohli; Alan Karthikesalingam; Simon Kohl; A. Taylan Cemgil; S. M. Ali Eslami; et al. (CoRR, 2020)

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)

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)

IBP Regularization for Verified Adversarial Robustness via Branch-and-Bound. - Alessandro De Palma; Rudy Bunel; Krishnamurthy Dvijotham; M. Pawan Kumar; Robert Stanforth (CoRR, 2022)

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)

Unlocking Accuracy and Fairness in Differentially Private Image Classification. - Leonard Berrada; Soham De; Judy Hanwen Shen; Jamie Hayes; Robert Stanforth; David Stutz; Pushmeet Kohli; Samuel L. Smith; Borja Balle (CoRR, 2023)

Expressive Losses for Verified Robustness via Convex Combinations. - Alessandro De Palma; Rudy Bunel; Krishnamurthy (Dj) Dvijotham; M. Pawan Kumar; Robert Stanforth; Alessio Lomuscio (ICLR, 2024)

Verified Neural Compressed Sensing. - Rudy Bunel; Krishnamurthy Dvijotham; M. Pawan Kumar; Alessandro De Palma; Robert Stanforth (CoRR, 2024)

Operationalizing Contextual Integrity in Privacy-Conscious Assistants. - Sahra Ghalebikesabi; Eugene Bagdasaryan; Ren Yi; Itay Yona; Ilia Shumailov; Aneesh Pappu; Chongyang Shi 003; Laura Weidinger; Robert Stanforth; Leonard Berrada; Pushmeet Kohli; Po-Sen Huang; et al. (CoRR, 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)

Privacy Awareness for Information-Sharing Assistants: A Case-study on Form-filling with Contextual Integrity. - Sahra Ghalebikesabi; Eugene Bagdasarian; Ren Yi; Itay Yona; Ilia Shumailov; Aneesh Pappu; Chongyang Shi 003; Laura Weidinger; Robert Stanforth; Leonard Berrada; Pushmeet Kohli; Po-Sen Huang; et al. (Trans. Mach. Learn. Res., 2025)