Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox
Picture for Alex Graudenzi

Alex Graudenzi
Alert button

Dept. of Informatics, Systems and Communication, University of Milan Bicocca

EAD: an ensemble approach to detect adversarial examples from the hidden features of deep neural networks


Nov 25, 2021
Francesco Craighero, Fabrizio Angaroni, Fabio Stella, Chiara Damiani, Marco Antoniotti, Alex Graudenzi

Add code
Alert button

Figure 1 for EAD: an ensemble approach to detect adversarial examples from the hidden features of deep neural networks
Figure 2 for EAD: an ensemble approach to detect adversarial examples from the hidden features of deep neural networks
Figure 3 for EAD: an ensemble approach to detect adversarial examples from the hidden features of deep neural networks
Figure 4 for EAD: an ensemble approach to detect adversarial examples from the hidden features of deep neural networks
* Corrected Figure 4 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Investigating the Compositional Structure Of Deep Neural Networks


Feb 17, 2020
Francesco Craighero, Fabrizio Angaroni, Alex Graudenzi, Fabio Stella, Marco Antoniotti

Add code
Alert button

Figure 1 for Investigating the Compositional Structure Of Deep Neural Networks
Figure 2 for Investigating the Compositional Structure Of Deep Neural Networks
Figure 3 for Investigating the Compositional Structure Of Deep Neural Networks
Figure 4 for Investigating the Compositional Structure Of Deep Neural Networks

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena


Oct 23, 2018
Daniele Ramazzotti, Marco S. Nobile, Marco Antoniotti, Alex Graudenzi

Add code
Alert button

Figure 1 for Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena
Figure 2 for Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena
Figure 3 for Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena
Figure 4 for Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Modeling cumulative biological phenomena with Suppes-Bayes Causal Networks


Jul 05, 2018
Daniele Ramazzotti, Alex Graudenzi, Giulio Caravagna, Marco Antoniotti

Add code
Alert button

Figure 1 for Modeling cumulative biological phenomena with Suppes-Bayes Causal Networks
Figure 2 for Modeling cumulative biological phenomena with Suppes-Bayes Causal Networks
Figure 3 for Modeling cumulative biological phenomena with Suppes-Bayes Causal Networks
Figure 4 for Modeling cumulative biological phenomena with Suppes-Bayes Causal Networks

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Learning mutational graphs of individual tumor evolution from multi-sample sequencing data


Sep 04, 2017
Daniele Ramazzotti, Alex Graudenzi, Luca De Sano, Marco Antoniotti, Giulio Caravagna

Add code
Alert button

Figure 1 for Learning mutational graphs of individual tumor evolution from multi-sample sequencing data
Figure 2 for Learning mutational graphs of individual tumor evolution from multi-sample sequencing data
Figure 3 for Learning mutational graphs of individual tumor evolution from multi-sample sequencing data
Figure 4 for Learning mutational graphs of individual tumor evolution from multi-sample sequencing data

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Proceedings Wivace 2013 - Italian Workshop on Artificial Life and Evolutionary Computation


Sep 27, 2013
Alex Graudenzi, Giulio Caravagna, Giancarlo Mauri, Marco Antoniotti

Add code
Alert button

* EPTCS 130, 2013 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email