16 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- CEA Paris-SaclayFR8 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR8 papers
- Centre National de la Recherche ScientifiqueFR7 papers
- Maison de la SimulationFR7 papers
- Université Paris-SaclayFR7 papers
- Centre de Mathématiques Appliquées de l'École polytechniqueFR5 papers
- École PolytechniqueFR5 papers
- Service d'Etudes Mécaniques et ThermiquesFR2 papers
- Département de Physique des ParticulesFR1 paper
- InsermFR1 paper
- Institut de Recherche sur les Lois Fondamentales de l'UniversFR1 paper
- Institut d'Imagerie BiomédicaleFR1 paper
9 papers
Robust a posteriori estimation of probit-lognormal seismic fragility curves via sequential design of experiments and constrained reference prior
Antoine Van Biesbroeck, Clément Gauchy, Cyril Feau +1
A seismic fragility curve expresses the probability of failure of a structure conditional to an intensity measure (IM) derived from seismic signals. When only limited data is avail…
Variational inference for approximate objective priors using neural networks
Nils Baillie, Antoine Van Biesbroeck, Clément Gauchy
In Bayesian statistics, the choice of the prior can have an important influence on the posterior and the parameter estimation, especially when few data samples are available. To li…
Cycle-Free Polytopal Mesh Sweeping for Boltzmann Transport
Ansar Calloo, Matthew Evans, Henry Lockyer +3
We introduce a novel property of bounded Voronoi tessellations that enables cycle-free mesh sweeping algorithms. We prove that a topological sort of the dual graph of any Voronoi t…
A short perspective on a posteriori error control and adaptive discretizations
Roland Becker, Stéphane P. A. Bordas, Franz Chouly +1
Error control by means of a posteriori error estimators or indica-tors and adaptive discretizations, such as adaptive mesh refinement, have emerged in the late seventies. Since the…
Revisiting Tensor Basis Neural Networks for Reynolds stress modeling: application to plane channel and square duct flows
Jiayi Cai, Pierre-Emmanuel Angeli, Jean-Marc Martinez +2
Several Tensor Basis Neural Network (TBNN) frameworks aimed at enhancing turbulence RANS modeling have recently been proposed in the literature as data-driven constitutive models f…
A unified two-scale gas-liquid multi-fluid model with capillarity and interface regularization through a mass transfer between scales
Arthur Loison, Samuel Kokh, Teddy Pichard +1
In this contribution, we derive a gas-liquid two-scale multi-fluid model with capillarity effects to enable a novelinterface regularization approach for multi-fluid models. As this…
Deep Learning reconstruction with uncertainty estimation for photon interaction in fast scintillator detectors
Geoffrey Daniel, Mohamed Bahi Yahiaoui, Claude Comtat +7
This article presents a physics-informed deep learning method for the quantitative estimation of the spatial coordinates of gamma interactions within a monolithic scintillator, wit…
Two-scale modelling of two-phase flows based on the Stationary Action Principle and a Geometric Method Of Moments
Arthur Loison, Teddy Pichard, Samuel Kokh +1
In this contribution, we introduce a versatile formalism to derive unified two-phase models describing both the separated and disperse regimes. It relies on the stationary action p…
Reference prior for Bayesian estimation of seismic fragility curves
Antoine Van Biesbroeck, Clement Gauchy, Cyril Feau +1
One of the key elements of probabilistic seismic risk assessment studies is the fragility curve, which represents the conditional probability of failure of a mechanical structure f…