deep learning


Formal verification of deep neural networks: theory and practice; a tutorial I gave during the joint INRIA-DFKI 2021 summer school.

Partitionnement en régions linéaires pour la vérification formelle de réseaux de neurones

La grande polyvalence et les résultats impressionnants des réseaux de neurones modernes viennent en partie de leur non-linéarité. Cette propriété fondamentale rend malheureusement très difficile leur vérification formelle, et ce, même si on se …

PFIA 2020

Theory and practice of deep learning verification; a tutorial I gave during the PFIA 2020 conference

CAMUS: A Framework to Build Formal Specifications for Deep Perception Systems Using Simulators

The topic of provable deep neural network robustness has raised considerable interest in recent years. Most research has focused on adversarial robustness, which studies the robustness of perceptive models in the neighbourhood of particular samples. …

ForMaL 2019

Some tutorial materials I gave with my advisor Guillaume Charpiat during DigiCOSME Spring school ForMaL

Automatic houseware registration system for informationally-structured environment

To provide daily-life assistance appropriately by a service robot, the management of houseware's information in a room or a house is an indispensable function. Especially, the information about what and where objects are in the environment are …