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08/28/2023
Distributionally Robust Statistical Verification with Imprecise Neural Networks
A particularly challenging problem in AI safety is providing guarantees ...
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02/21/2023
Using Semantic Information for Defining and Detecting OOD Inputs
As machine learning models continue to achieve impressive performance ac...
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02/20/2023
Take Me Home: Reversing Distribution Shifts using Reinforcement Learning
Deep neural networks have repeatedly been shown to be non-robust to the ...
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02/19/2023
Imprecise Bayesian Neural Networks
Uncertainty quantification and robustness to distribution shifts are imp...
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12/02/2022
Guaranteed Conformance of Neurosymbolic Models to Natural Constraints
Deep neural networks have emerged as the workhorse for a large section o...
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06/13/2022
Towards Alternative Techniques for Improving Adversarial Robustness: Analysis of Adversarial Training at a Spectrum of Perturbations
Adversarial training (AT) and its variants have spearheaded progress in ...
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06/10/2022
Memory Classifiers: Two-stage Classification for Robustness in Machine Learning
The performance of machine learning models can significantly degrade und...
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02/25/2022
Exploring with Sticky Mittens: Reinforcement Learning with Expert Interventions via Option Templates
Environments with sparse rewards and long horizons pose a significant ch...
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09/26/2017