Search Results for author: Luca Cardelli

Found 9 papers, 4 papers with code

A Language for Modeling And Optimizing Experimental Biological Protocols

no code implementations13 Jun 2021 Luca Cardelli, Marta Kwiatkowska, Luca Laurenti

We should ideally start from an integrated description of both the model and the steps carried out to test it, to concurrently analyze uncertainties in model parameters, equipment tolerances, and data collection.

Adversarial Robustness Guarantees for Gaussian Processes

1 code implementation7 Apr 2021 Andrea Patane, Arno Blaas, Luca Laurenti, Luca Cardelli, Stephen Roberts, Marta Kwiatkowska

Gaussian processes (GPs) enable principled computation of model uncertainty, making them attractive for safety-critical applications.

Adversarial Robustness Gaussian Processes

Exact maximal reduction of stochastic reaction networks by species lumping

no code implementations9 Jan 2021 Luca Cardelli, Isabel Cristina Perez-Verona, Mirco Tribastone, Max Tschaikowski, Andrea Vandin, Tabea Waizmann

Motivation: Stochastic reaction networks are a widespread model to describe biological systems where the presence of noise is relevant, such as in cell regulatory processes.

Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control

no code implementations21 Sep 2019 Rhiannon Michelmore, Matthew Wicker, Luca Laurenti, Luca Cardelli, Yarin Gal, Marta Kwiatkowska

Deep neural network controllers for autonomous driving have recently benefited from significant performance improvements, and have begun deployment in the real world.

Autonomous Driving Bayesian Inference +3

Adversarial Robustness Guarantees for Classification with Gaussian Processes

1 code implementation28 May 2019 Arno Blaas, Andrea Patane, Luca Laurenti, Luca Cardelli, Marta Kwiatkowska, Stephen Roberts

We apply our method to investigate the robustness of GPC models on a 2D synthetic dataset, the SPAM dataset and a subset of the MNIST dataset, providing comparisons of different GPC training techniques, and show how our method can be used for interpretability analysis.

Adversarial Robustness Classification +2

Statistical Guarantees for the Robustness of Bayesian Neural Networks

1 code implementation5 Mar 2019 Luca Cardelli, Marta Kwiatkowska, Luca Laurenti, Nicola Paoletti, Andrea Patane, Matthew Wicker

We introduce a probabilistic robustness measure for Bayesian Neural Networks (BNNs), defined as the probability that, given a test point, there exists a point within a bounded set such that the BNN prediction differs between the two.

General Classification Image Classification

Robustness Guarantees for Bayesian Inference with Gaussian Processes

1 code implementation17 Sep 2018 Luca Cardelli, Marta Kwiatkowska, Luca Laurenti, Andrea Patane

Bayesian inference and Gaussian processes are widely used in applications ranging from robotics and control to biological systems.

Bayesian Inference Gaussian Processes

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