
Certification of Iterative Predictions in Bayesian Neural Networks
We consider the problem of computing reachavoid probabilities for itera...
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Bayesian Inference with Certifiable Adversarial Robustness
We consider adversarial training of deep neural networks through the len...
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GradientFree Adversarial Attacks for Bayesian Neural Networks
The existence of adversarial examples underscores the importance of unde...
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Probabilistic Safety for Bayesian Neural Networks
We study probabilistic safety for Bayesian Neural Networks (BNNs) under ...
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Robustness of Bayesian Neural Networks to GradientBased Attacks
Vulnerability to adversarial attacks is one of the principal hurdles to ...
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Uncertainty Quantification with Statistical Guarantees in EndtoEnd Autonomous Driving Control
Deep neural network controllers for autonomous driving have recently ben...
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Robustness of 3D Deep Learning in an Adversarial Setting
Understanding the spatial arrangement and nature of realworld objects i...
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Statistical Guarantees for the Robustness of Bayesian Neural Networks
We introduce a probabilistic robustness measure for Bayesian Neural Netw...
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A GameBased Approximate Verification of Deep Neural Networks with Provable Guarantees
Despite the improved accuracy of deep neural networks, the discovery of ...
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Efficient Learning of Optimal Markov Network Topology with kTree Modeling
The seminal work of Chow and Liu (1968) shows that approximation of a fi...
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FeatureGuided BlackBox Safety Testing of Deep Neural Networks
Despite the improved accuracy of deep neural networks, the discovery of ...
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Matthew Wicker
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