425 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre National de la Recherche ScientifiqueFR43 papers
- EDF Energy (United Kingdom)GB24 papers
- CERMICSFR17 papers
- Université Paris-SaclayFR17 papers
- Institut de Mathématiques de ToulouseFR16 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR14 papers
- Institut national de recherche en sciences et technologies du numériqueFR14 papers
- Laboratoire de Probabilités, Statistique et ModélisationFR14 papers
- Université Toulouse III - Paul SabatierFR13 papers
- Centre de Mathématiques Appliquées de l'École polytechniqueFR12 papers
- École PolytechniqueFR12 papers
- Laboratoire de Probabilités et Modèles AléatoiresFR12 papers
17 papers · 1 filter
Hubbard physics with Rydberg atoms: using a quantum spin simulator to simulate strong fermionic correlations
Antoine Michel, Loïc Henriet, Christophe Domain +2
We propose a hybrid quantum-classical method to investigate the equilibrium physics and the dynamics of strongly correlated fermionic models with spin-based quantum processors. Our…
Efficient Model-Based Concave Utility Reinforcement Learning through Greedy Mirror Descent
Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard +1
Many machine learning tasks can be solved by minimizing a convex function of an occupancy measure over the policies that generate them. These include reinforcement learning, imitat…
Identification of vortex in unstructured mesh with graph neural networks
Lianfa Wang, Yvan Fournier, Jean-Francois Wald +1
Deep learning has been employed to identify flow characteristics from Computational Fluid Dynamics (CFD) databases to assist the researcher to better understand the flow field, to…
Human Reliability Assessment method applied to investigate human factors in NDT -- The case of the interpretation of radiograms in the French nuclear sector
Justin Larouze, Etienne Martin, Pierre Calmon
This communication reports on a study carried out in the context of the collaborative FOEHN project (Human and Organizational Factors in Non-Destructive Evaluation) supported by th…
PyPVRoof: a Python package for extracting the characteristics of rooftop PV installations using remote sensing data
Yann Tremenbert, Gabriel Kasmi, Laurent Dubus +2
Photovoltaic (PV) energy grows at an unprecedented pace, which makes it difficult to maintain up-to-date and accurate PV registries, which are critical for many applications such a…
A collinear-spin machine learned interatomic potential for FeCrNi alloy
Lakshmi Shenoy, Christopher D. Woodgate, Julie B. Staunton +4
We have developed a new machine learned interatomic potential for the prototypical austenitic steel FeCrNi, using the Gaussian approximation potential (GAP) framework.…
An entropy penalized approach for stochastic control problems. Complete version
Thibaut Bourdais, Nadia Oudjane, Francesco Russo
In this paper, we propose an original approach to stochastic control problems. We consider a weak formulation that is written as an optimization (minimization) problem on the space…
Capacity ATL
Gabriel Ballot, Vadim Malvone, Jean Leneutre +1
Model checking strategic abilities was successfully developed and applied since the early 2000s to ensure properties in Multi-Agent System. In this paper, we introduce the notion o…
Forecasting Electric Vehicle Charging Station Occupancy: Smarter Mobility Data Challenge
Yvenn Amara-Ouali, Yannig Goude, Nathan Doumèche +10
The transport sector is a major contributor to greenhouse gas emissions in Europe. Shifting to electric vehicles (EVs) powered by a low-carbon energy mix would reduce carbon emissi…
Conformal Prediction with Missing Values
Margaux Zaffran, Aymeric Dieuleveut, Julie Josse +1
Conformal prediction is a theoretically grounded framework for constructing predictive intervals. We study conformal prediction with missing values in the covariates -- a setting t…
Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations
Etienne Le Naour, Louis Serrano, Léon Migus +5
We introduce a novel modeling approach for time series imputation and forecasting, tailored to address the challenges often encountered in real-world data, such as irregular sample…
Appliance Detection Using Very Low-Frequency Smart Meter Time Series
Adrien Petralia, Philippe Charpentier, Paul Boniol +1
In recent years, smart meters have been widely adopted by electricity suppliers to improve the management of the smart grid system. These meters usually collect energy consumption…
Assessment of the Reliablity of a Model's Decision by Generalizing Attribution to the Wavelet Domain
Gabriel Kasmi, Laurent Dubus, Yves-Marie Saint Drenan +1
Neural networks have shown remarkable performance in computer vision, but their deployment in numerous scientific and technical fields is challenging due to their black-box nature.…
Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents
Malte Lehna, Jan Viebahn, Christoph Scholz +2
The operation of electricity grids has become increasingly complex due to the current upheaval and the increase in renewable energy production. As a consequence, active grid manage…
Frugal day-ahead forecasting of multiple local electricity loads by aggregating adaptive models
Guillaume Lambert, Bachir Hamrouche, Joseph de Vilmarest
We focus on day-ahead electricity load forecasting of substations of the distribution network in France; therefore, our problem lies between the instability of a single consumption…
Reimagining Demand-Side Management with Mean Field Learning
Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard +1
Integrating renewable energy into the power grid while balancing supply and demand is a complex issue, given its intermittent nature. Demand side management (DSM) offers solutions…
A blueprint for a Digital-Analog Variational Quantum Eigensolver using Rydberg atom arrays
Antoine Michel, Sebastian Grijalva, Loïc Henriet +2
We address the task of estimating the ground-state energy of Hamiltonians coming from chemistry. We study numerically the behavior of a digital-analog variational quantum eigensolv…