◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Ginevra Carbone

4 papers hereh-index 5142 citations12 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • eess.SY1
ORCID 0000-0001-7532-6249

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.LG2021

Abstraction of Markov Population Dynamics via Generative Adversarial Nets

Francesca Cairoli, Ginevra Carbone, Luca Bortolussi

Markov Population Models are a widespread formalism used to model the dynamics of complex systems, with applications in Systems Biology and many other fields. The associated Markov…

cs.LG2021

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…

eess.SY2020

Adversarial Learning of Robust and Safe Controllers for Cyber-Physical Systems

Luca Bortolussi, Francesca Cairoli, Ginevra Carbone +2

We introduce a novel learning-based approach to synthesize safe and robust controllers for autonomous Cyber-Physical Systems and, at the same time, to generate challenging tests. T…

cs.LG2020

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…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.