Robert Stanforth

According to our database1, Robert Stanforth authored at least 24 papers between 2018 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Operationalizing Contextual Integrity in Privacy-Conscious Assistants.
CoRR, 2024

Verified Neural Compressed Sensing.
CoRR, 2024

Expressive Losses for Verified Robustness via Convex Combinations.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Unlocking Accuracy and Fairness in Differentially Private Image Classification.
CoRR, 2023

Differentially Private Diffusion Models Generate Useful Synthetic Images.
CoRR, 2023

2022
IBP Regularization for Verified Adversarial Robustness via Branch-and-Bound.
CoRR, 2022

2021
Verifying Probabilistic Specifications with Functional Lagrangians.
CoRR, 2021

Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications.
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.
CoRR, 2020

Towards Stable and Efficient Training of Verifiably Robust Neural Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control.
Proceedings of the 8th International Conference on Learning Representations, 2020

Towards Verified Robustness under Text Deletion Interventions.
Proceedings of the 8th International Conference on Learning Representations, 2020

Reducing Sentiment Bias in Language Models via Counterfactual Evaluation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

2019
Efficient Neural Network Verification with Exactness Characterization.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Adversarial Robustness through Local Linearization.
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?
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.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Verification of Non-Linear Specifications for Neural Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

Scalable Verified Training for Provably Robust Image Classification.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation.
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.
CoRR, 2018

On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models.
CoRR, 2018

Training verified learners with learned verifiers.
CoRR, 2018

A Dual Approach to Scalable Verification of Deep Networks.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018


  Loading...