13 citations
- Centre National de la Recherche ScientifiqueFR45 papers
- Centre de Recherche en Informatique, Signal et Automatique de LilleFR32 papers
- École Centrale de LilleFR31 papers
- Université Paris CitéFR26 papers
- Institut d'Astrophysique SpatialeFR25 papers
- Sorbonne UniversitéFR25 papers
- Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des ParticulesFR24 papers
- Centre de physique des particules de MarseilleFR24 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR24 papers
- Observatoire astronomique de StrasbourgFR24 papers
- Université Paris-SaclayFR24 papers
- Astrophysique, Instrumentation et ModélisationFR23 papers
5 papers · 1 filter
Data-Driven Fire-Zone Segmentation for Improved Short-Term Wildfire Prediction
Nicolas Caron, Christophe Guyeux, Hassan Noura +1
Wildfire prediction models typically discretize study areas into uniform grids, ignoring the heterogeneous spatial distribution of ignitions. We challenge this paradigm by showing…
Quenched large deviations for Monte Carlo integration with Coulomb gases
Martin Rouault, Rémi Bardenet, Mylène Maïda
Gibbs measures, such as Coulomb gases, are popular in modelling systems of interacting particles. Recently, we proposed to use Gibbs measures as randomized numerical integration al…
Monte Carlo with kernel-based Gibbs measures: Guarantees for probabilistic herding
Martin Rouault, Rémi Bardenet, Mylène Maïda
Kernel herding belongs to a family of deterministic quadratures that seek to minimize the maximum mean discrepancy (MMD), that is, the worst-case integration error over a reproduci…
On two ways to use determinantal point processes for Monte Carlo integration
Guillaume Gautier, Rémi Bardenet, Michal Valko
The standard Monte Carlo estimator of relies on independent samples from and has variance of order . Replacing the samples with…
Learning to Explore with Lagrangians for Bandits under Unknown Linear Constraints
Udvas Das, Debabrota Basu
Pure exploration in bandits formalises multiple real-world problems, such as tuning hyper-parameters or conducting user studies to test a set of items, where different safety, reso…