339 citations
- Centre National de la Recherche ScientifiqueFR30 papers
- Laboratoire d'Informatique Gaspard-MongeFR15 papers
- Sorbonne UniversitéFR9 papers
- Université Gustave EiffelFR7 papers
- Université Paris-SaclayFR7 papers
- Institut national de recherche en sciences et technologies du numériqueFR6 papers
- CentraleSupélecFR5 papers
- Institut de Mathématiques de ToulouseFR5 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR4 papers
- Lyon 1 UniversitéFR4 papers
- Université Paris-Est Marne-la-ValléeFR4 papers
- Université Toulouse III - Paul SabatierFR4 papers
8 papers · 1 filter
Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention
Léo Hein, Giovanni de Nunzio, Giovanni Chierchia +2
Existing traffic volume estimation methods typically address either forecasting traffic on sensor-equipped roads or spatially imputing missing volumes using nearby sensors. While f…
WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm Control
Claire Bizon Monroc, Ana Bušić, Donatien Dubuc +1
The wind farm control problem is challenging, since conventional model-based control strategies require tractable models of complex aerodynamical interactions between the turbines…
Reinforcement Learning and Regret Bounds for Admission Control
Lucas Weber, Ana Bušić, Jiamin Zhu
The expected regret of any reinforcement learning algorithm is lower bounded by for undiscounted returns, where is the diameter of the Markov decisi…
Multi-Level GNN Preconditioner for Solving Large Scale Problems
Matthieu Nastorg, Jean-Marc Gratien, Thibault Faney +3
Large-scale numerical simulations often come at the expense of daunting computations. High-Performance Computing has enhanced the process, but adapting legacy codes to leverage par…
SWMLP: Shared Weight Multilayer Perceptron for Car Trajectory Speed Prediction using Road Topographical Features
Sarah Almeida Carneiro, Giovanni Chierchia, Jean Charléty +2
Although traffic is one of the massively collected data, it is often only available for specific regions. One concern is that, although there are studies that give good results for…
An Implicit GNN Solver for Poisson-like problems
Matthieu Nastorg, Michele Alessandro Bucci, Thibault Faney +3
This paper presents -GNN, a novel Graph Neural Network (GNN) approach for solving the ubiquitous Poisson PDE problems with mixed boundary conditions. By leveraging the Implicit…