
Certification of Iterative Predictions in Bayesian Neural Networks
We consider the problem of computing reachavoid probabilities for itera...
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Adversarial Robustness Guarantees for Gaussian Processes
Gaussian processes (GPs) enable principled computation of model uncertai...
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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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Assessing Robustness of Text Classification through Maximal Safe Radius Computation
Neural network NLP models are vulnerable to small modifications of the i...
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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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Safety Guarantees for Planning Based on Iterative Gaussian Processes
Gaussian Processes (GPs) are widely employed in control and learning bec...
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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 Quantification for Classification with Gaussian Processes
We consider Bayesian classification with Gaussian processes (GPs) and de...
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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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Robustness Guarantees for Bayesian Inference with Gaussian Processes
Bayesian inference and Gaussian processes are widely used in application...
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Central Limit Model Checking
We consider probabilistic model checking for continuoustime Markov chai...
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Experimental Biological Protocols with Formal Semantics
Both experimental and computational biology is becoming increasingly aut...
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Luca Laurenti
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