Rudy Bunel

According to our database, Rudy Bunel authored at least 31 papers between 2016 and 2023.

Collaborative distances:

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

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

Faithful Knowledge Distillation.

Tom A. Lamb, Rudy Bunel, Krishnamurthy (Dj) Dvijotham, M. Pawan Kumar, Philip H. S. Torr, Francisco Eiras

CoRR, 2023

Expressive Losses for Verified Robustness via Convex Combinations.

Alessandro De Palma, Rudy Bunel, Krishnamurthy Dvijotham, M. Pawan Kumar, Robert Stanforth, Alessio Lomuscio

CoRR, 2023

Provably Correct Physics-Informed Neural Networks.

Francisco Eiras, Adel Bibi, Rudy Bunel, Krishnamurthy (Dj) Dvijotham, Philip H. S. Torr, M. Pawan Kumar

CoRR, 2023

2022

IBP Regularization for Verified Adversarial Robustness via Branch-and-Bound.

Alessandro De Palma, Rudy Bunel, Krishnamurthy Dvijotham, M. Pawan Kumar, Robert Stanforth

CoRR, 2022

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

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

Scaling the Convex Barrier with Sparse Dual Algorithms.

Alessandro De Palma, Harkirat Singh Behl, Rudy Bunel, Philip H. S. Torr, M. Pawan Kumar

CoRR, 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

Scaling the Convex Barrier with Active Sets.

Alessandro De Palma, Harkirat S. Behl, Rudy Bunel, Philip H. S. Torr, M. Pawan Kumar

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

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

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, Olaf Ronneberger

CoRR, 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

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

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

An efficient nonconvex reformulation of stagewise convex optimization problems.

Rudy Bunel, Oliver Hinder, Srinadh Bhojanapalli, Krishnamurthy Dvijotham

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

2019

Formal verification of neural networks

Rudy Bunel

PhD thesis, 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

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

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

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

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

A Unified View of Piecewise Linear Neural Network Verification.

Rudy Bunel, Ilker Turkaslan, Philip H. S. Torr, Pushmeet Kohli, Pawan Kumar Mudigonda

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis.

Rudy Bunel, Matthew J. Hausknecht, Jacob Devlin, Rishabh Singh, Pushmeet Kohli

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Piecewise Linear Neural Network verification: A comparative study.

Rudy Bunel, Ilker Turkaslan, Philip H. S. Torr, Pushmeet Kohli, M. Pawan Kumar

CoRR, 2017

Neural Program Meta-Induction.

Jacob Devlin, Rudy Bunel, Rishabh Singh, Matthew J. Hausknecht, Pushmeet Kohli

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

Learning to superoptimize programs.

Rudy Bunel, Alban Desmaison, M. Pawan Kumar, Philip H. S. Torr, Pushmeet Kohli

Proceedings of the 5th International Conference on Learning Representations, 2017

Efficient Linear Programming for Dense CRFs.

Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel, Mathieu Salzmann, Philip H. S. Torr, M. Pawan Kumar

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Learning to superoptimize programs - Workshop Version.

Rudy Bunel, Alban Desmaison, M. Pawan Kumar, Philip H. S. Torr, Pushmeet Kohli

CoRR, 2016

Adaptive Neural Compilation.

Rudy Bunel, Alban Desmaison, Pawan Kumar Mudigonda, Pushmeet Kohli, Philip H. S. Torr

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Detection of pedestrians at far distance.

Rudy Bunel, Franck Davoine, Philippe Xu

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Efficient Continuous Relaxations for Dense CRF.

Alban Desmaison, Rudy Bunel, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar

Proceedings of the Computer Vision - ECCV 2016, 2016