Robert Stanforth

According to our database, Robert Stanforth authored at least 22 papers between 2018 and 2023.

Collaborative distances:

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

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 Dvijotham, M. Pawan Kumar, Robert Stanforth, Alessio Lomuscio

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

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

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

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

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

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

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

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

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

Are Labels Required for Improving Adversarial Robustness?

Jean-Baptiste Alayrac, Jonathan Uesato, Po-Sen Huang, Alhussein Fawzi, 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

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

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

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

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

Training verified learners with learned verifiers.

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

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