Efficient Continuous Relaxations for Dense CRF. - Alban Desmaison; Rudy Bunel; Pushmeet Kohli; Philip H. S. Torr; M. Pawan Kumar (ECCV (2), 2016)

Detection of pedestrians at far distance. - Rudy Bunel; Franck Davoine; Philippe Xu (ICRA, 2016)

Adaptive Neural Compilation. - Rudy Bunel; Alban Desmaison; Pawan Kumar Mudigonda; Pushmeet Kohli; Philip H. S. Torr (NIPS, 2016)

Learning to superoptimize programs - Workshop Version. - Rudy Bunel; Alban Desmaison; M. Pawan Kumar; Philip H. S. Torr; Pushmeet Kohli (CoRR, 2016)

Efficient Linear Programming for Dense CRFs. - Thalaiyasingam Ajanthan; Alban Desmaison; Rudy Bunel; Mathieu Salzmann; Philip H. S. Torr; M. Pawan Kumar (CVPR, 2017)

Learning to superoptimize programs. - Rudy Bunel; Alban Desmaison; M. Pawan Kumar; Philip H. S. Torr; Pushmeet Kohli (ICLR (Poster), 2017)

Neural Program Meta-Induction. - Jacob Devlin; Rudy Bunel; Rishabh Singh; Matthew J. Hausknecht; Pushmeet Kohli (NIPS, 2017)

Piecewise Linear Neural Network verification: A comparative study. - Rudy Bunel; Ilker Turkaslan; Philip H. S. Torr; Pushmeet Kohli; M. Pawan Kumar (CoRR, 2017)

Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis. - Rudy Bunel; Matthew J. Hausknecht; Jacob Devlin; Rishabh Singh; Pushmeet Kohli (ICLR (Poster), 2018)

A Unified View of Piecewise Linear Neural Network Verification. - Rudy Bunel; Ilker Turkaslan; Philip H. S. Torr; Pushmeet Kohli; Pawan Kumar Mudigonda (NeurIPS, 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)

Knowing When to Stop: Evaluation and Verification of Conformity to Output-Size Specifications. - Chenglong Wang; Rudy Bunel; Krishnamurthy Dvijotham; Po-Sen Huang; Edward Grefenstette; Pushmeet Kohli (CVPR, 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)

Efficient Relaxations for Dense CRFs with Sparse Higher-Order Potentials. - Thomas Joy; Alban Desmaison; Thalaiyasingam Ajanthan; Rudy Bunel; Mathieu Salzmann; Pushmeet Kohli; Philip H. S. Torr; M. Pawan Kumar (SIAM J. Imaging Sci., 2019)

Formal verification of neural networks - Rudy Bunel (2019)

An efficient nonconvex reformulation of stagewise convex optimization problems. - Rudy Bunel; Oliver Hinder; Srinadh Bhojanapalli; Krishnamurthy Dvijotham (NeurIPS, 2020)

Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming. - Sumanth Dathathri; Krishnamurthy Dvijotham; Alexey Kurakin; Aditi Raghunathan; Jonathan Uesato; Rudy Bunel; Shreya Shankar; Jacob Steinhardt; Ian J. Goodfellow; Percy Liang; Pushmeet Kohli (NeurIPS, 2020)

Lagrangian Decomposition for Neural Network Verification. - Rudy Bunel; Alessandro De Palma; Alban Desmaison; Krishnamurthy Dvijotham; Pushmeet Kohli; Philip H. S. Torr; M. Pawan Kumar (UAI, 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)

Branch and Bound for Piecewise Linear Neural Network Verification. - Rudy Bunel; Jingyue Lu; Ilker Turkaslan; Philip H. S. Torr; Pushmeet Kohli; M. Pawan Kumar (J. Mach. Learn. Res., 2020)

Scaling the Convex Barrier with Active Sets. - Alessandro De Palma; Harkirat S. Behl; Rudy Bunel; Philip H. S. Torr; M. Pawan Kumar (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)

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)

Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition. - Alessandro De Palma; Rudy Bunel; Alban Desmaison; Krishnamurthy Dvijotham; Pushmeet Kohli; Philip H. S. Torr; 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)

Provably Correct Physics-Informed Neural Networks. - Francisco Eiras; Adel Bibi; Rudy Bunel; Krishnamurthy (Dj) Dvijotham; Philip H. S. Torr; M. Pawan Kumar (CoRR, 2023)

Faithful Knowledge Distillation. - Tom A. Lamb; Rudy Bunel; Krishnamurthy (Dj) Dvijotham; M. Pawan Kumar; Philip H. S. Torr; Francisco Eiras (CoRR, 2023)

DRIP: Domain Refinement Iteration With Polytopes for Backward Reachability Analysis of Neural Feedback Loops. - Michael Everett; Rudy Bunel; Shayegan Omidshafiei (IEEE Control. Syst. Lett., 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)

Efficient Error Certification for Physics-Informed Neural Networks. - Francisco Eiras; Adel Bibi; Rudy Bunel; Krishnamurthy Dj Dvijotham; Philip Torr 001; M. Pawan Kumar (ICML, 2024)

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

Imagen 3. - Jason Baldridge; Jakob Bauer; Mukul Bhutani; Nicole Brichtova; Andrew Bunner; Kelvin Chan; Yichang Chen; Sander Dieleman; Yuqing Du; Zach Eaton-Rosen; Hongliang Fei; Nando de Freitas; et al. (CoRR, 2024)

Scaling the Convex Barrier with Sparse Dual Algorithms. - Alessandro De Palma; Harkirat Singh Behl; Rudy Bunel; Philip H. S. Torr; M. Pawan Kumar (J. Mach. Learn. Res., 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)