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
102 papers
Nix to the Rescue for a Reproducible HPC-AI Software Stack
Wenke Du, Jean-Marc Gratien, Raphael Gayno +1
Reproducibility in HPC remains difficult under the constraints of production supercomputers: no root access, limited internet, and software stacks that increasingly span C/C++, For…
The BRUIT-FM "open data" noise reduction challenge
Wayne C Crawford, Stephan Ker, Simon Rebeyrol +1
The BRUIT-FM Challenge asks participants to reduce ''noise'' on an open dataset of real and synthetic broadband seafloor seismology data. The dataset includes signals from earthqua…
Proportional dispatch and fairness in wind farm power tracking
Baptiste Corban, Ana Bušić, Donatien Dubuc +1
Controlling the power output of a wind farm to track a target signal enables contributing to the power grid stability. This can be achieved by dividing the target signal into indiv…
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…
Analyse comparative d'algorithmes de restauration en architecture dépliée pour des signaux chromatographiques parcimonieux
Mouna Gharbi, Silvia Villa, Emilie Chouzenoux +2
Data restoration from degraded observations, of sparsity hypotheses, is an active field of study. Traditional iterative optimization methods are now complemented by deep learning t…
LUNDIsim: model meshes for flow simulation and scientific data compression benchmarks
Laurent Duval, Frédéric Payan, Christophe Preux +1
The volume of scientific data produced for and by numerical simulation workflows is increasing at an incredible rate. This raises concerns either in computability, interpretability…