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06/23/2023
Adversarial Robustness Certification for Bayesian Neural Networks
We study the problem of certifying the robustness of Bayesian neural net...
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04/21/2023
Individual Fairness in Bayesian Neural Networks
We study Individual Fairness (IF) for Bayesian neural networks (BNNs). S...
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03/11/2023
Robust Learning from Explanations
Machine learning from explanations (MLX) is an approach to learning that...
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12/16/2022
Robust Explanation Constraints for Neural Networks
Post-hoc explanation methods are used with the intent of providing insig...
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10/31/2022
Emergent Linguistic Structures in Neural Networks are Fragile
Large language models (LLMs) have been reported to have strong performan...
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07/13/2022
On the Robustness of Bayesian Neural Networks to Adversarial Attacks
Vulnerability to adversarial attacks is one of the principal hurdles to ...
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05/11/2022
Individual Fairness Guarantees for Neural Networks
We consider the problem of certifying the individual fairness (IF) of fe...
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04/29/2022
Tractable Uncertainty for Structure Learning
Bayesian structure learning allows one to capture uncertainty over the c...
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05/21/2021
Certification of Iterative Predictions in Bayesian Neural Networks
We consider the problem of computing reach-avoid probabilities for itera...
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02/10/2021
Bayesian Inference with Certifiable Adversarial Robustness
We consider adversarial training of deep neural networks through the len...
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12/23/2020
Gradient-Free Adversarial Attacks for Bayesian Neural Networks
The existence of adversarial examples underscores the importance of unde...
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04/21/2020
Probabilistic Safety for Bayesian Neural Networks
We study probabilistic safety for Bayesian Neural Networks (BNNs) under ...
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02/11/2020
Robustness of Bayesian Neural Networks to Gradient-Based Attacks
Vulnerability to adversarial attacks is one of the principal hurdles to ...
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09/21/2019
Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control
Deep neural network controllers for autonomous driving have recently ben...
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04/01/2019
Robustness of 3D Deep Learning in an Adversarial Setting
Understanding the spatial arrangement and nature of real-world objects i...
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03/05/2019
Statistical Guarantees for the Robustness of Bayesian Neural Networks
We introduce a probabilistic robustness measure for Bayesian Neural Netw...
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07/10/2018
A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees
Despite the improved accuracy of deep neural networks, the discovery of ...
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01/21/2018
Efficient Learning of Optimal Markov Network Topology with k-Tree Modeling
The seminal work of Chow and Liu (1968) shows that approximation of a fi...
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10/21/2017