Frederic Barbaresco — accepted AI-conference papers

2025

Hybrid Quantum-Classical Multi-Agent Pathfinding

Thore Gerlach, Loong Kuan Lee, Frederic BARBARESCO, Nico Piatkowski

ICML 2025poster

Multi-Agent Path Finding (MAPF) focuses on determining conflict-free paths for multiple agents navigating through a shared space to reach specified goal locations. This problem becomes computationally challenging, particularly when handling large numbers of agents, as frequently encountered in prac…

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2019

Riemannian batch normalization for SPD neural networks

Daniel Brooks, Olivier Schwander, Frederic Barbaresco, Jean-Yves Schneider, Matthieu Cord

NeurIPS 2019poster

Covariance matrices have attracted attention for machine learning applications due to their capacity to capture interesting structure in the data. The main challenge is that one needs to take into account the particular geometry of the Riemannian manifold of symmetric positive definite (SPD) matrice…

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