Although neural networks are effective tools for processing information from image-based
sensors to produce control actions, their complex nature limits their use in safety-critical …

Enabled by recent advances in the field of machine learning, the automotive industry pushes
towards automated driving. The development of traditional safety-critical automotive …

As AI systems are becoming more and more popular and used in various critical domains
(health, transport, energy,...), the need to provide guarantees and trust of their safety is …

M in its cosmos of tasks, models, and methods is as diverse as ever.
While traditionally, we have distinguished only supervised learning tasks like classification …

The field of Formal Methods may very well be one of the oldest fields in Computer Science,
but it has been brought back to its infancy with the recent advances in Machine Learning. As …

Abstract Machine learning has the potential to unlock a variety of new capabilities for the
automation of safety-critical systems. For example, it can be used in the aviation domain to …

We explored the potential contribution of eXplainable Artificial Intelligence (XAI) for the
evaluation of Artificial Intelligence (AI), in a context where such an evaluation is performed …

Résumé Les codes de simulation numérique industriels sont basés le plus souvent sur une
modélisation hypothético-déductive permettant d'obtenir des avancées significatives sur la …

This project is housed at the Institute of Futures Research and relates to understanding and
regularizing challenges to goal and value alignment in artificial intelligent (AI) systems when …

Avec le renouveau de l'IA, on assiste aujourd'hui à une croissance de ses usages, sans
précédent. Ce qui a changé ces dernières années, c'est que la recherche est passée de …