19 citations · 26 across the 6 of their papers we have counts for
13 papers
Bayesian learning of effective chemical master equations in crowded intracellular conditions
Svitlana Braichenko, Ramon Grima, Guido Sanguinetti
Biochemical reactions inside living cells often occur in the presence of crowders -- molecules that do not participate in the reactions but influence the reaction rates through exc…
Random Projections for Improved Adversarial Robustness
Ginevra Carbone, Guido Sanguinetti, Luca Bortolussi
We propose two training techniques for improving the robustness of Neural Networks to adversarial attacks, i.e. manipulations of the inputs that are maliciously crafted to fool net…
Systematic errors in estimates of from symptomatic cases in the presence of observation bias
Guido Sanguinetti
We consider the problem of estimating the reproduction number of an epidemic for populations where the probability of detection of cases depends on a known covariate. We argu…
Estimating the impact of preventive quarantine with reverse epidemiology
Jacopo Grilli, Matteo Marsili, Guido Sanguinetti
The impact of mitigation or control measures on an epidemics can be estimated by fitting the parameters of a compartmental model to empirical data, and running the model forward wi…
Robustness of Bayesian Neural Networks to Gradient-Based Attacks
Ginevra Carbone, Matthew Wicker, Luca Laurenti +3
Vulnerability to adversarial attacks is one of the principal hurdles to the adoption of deep learning in safety-critical applications. Despite significant efforts, both practical a…
Parameter estimation for biochemical reaction networks using Wasserstein distances
Kaan Öcal, Ramon Grima, Guido Sanguinetti
We present a method for estimating parameters in stochastic models of biochemical reaction networks by fitting steady-state distributions using Wasserstein distances. We simulate a…