44 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Électricité de France (France)FR5 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- Institut de Mathématiques de ToulouseFR2 papers
- Centre Inria de l'Université Grenoble AlpesFR1 paper
- Centre Inria de SaclayFR1 paper
- Cristal (United Kingdom)GB1 paper
- École nationale des ponts et chausséesFR1 paper
- École Nationale Supérieure de Techniques AvancéesFR1 paper
- EDF Energy (United Kingdom)GB1 paper
- Gouvernance, Risque, Environnement, DéveloppementFR1 paper
- Grains Research and Development CorporationAU1 paper
- Hong Kong Baptist UniversityHK1 paper
10 papers
A User-oriented Portable, Reproducible, and Scalable Software Ecosystem
Alfio Lazzaro, Utz-Uwe Haus, Sandrine Charousset +1
It is normal for scientists to perform their research on a diverse set of hardware, ranging from laptops and workstations to supercomputers and cloud resources. The standard scenar…
The influence of grain crushing and pore collapse on the formation of faults
N. A. Collins-Craft, I. Stefanou, J. Sulem +1
During an earthquake, slip occurs in a localised shear zone that features a heavily granulated fault core that can be characterised as a shear band. We study the formation of this…
Fast Gaussian process inference by exact Matérn kernel decomposition
Nicolas Langrené, Xavier Warin, Pierre Gruet
To speed up Gaussian process inference, a number of fast kernel matrix-vector multiplication (MVM) approximation algorithms have been proposed over the years. In this paper, we est…
A Fast Learning-Based Surrogate of Electrical Machines using a Reduced Basis
Alejandro Ribés, Nawfal Benchekroun, Théo Delagnes
A surrogate model approximates the outputs of a solver of Partial Differential Equations (PDEs) with a low computational cost. In this article, we propose a method to build learnin…
High Throughput Training of Deep Surrogates from Large Ensemble Runs
Lucas Meyer, Marc Schouler, Robert Alexander Caulk +2
Recent years have seen a surge in deep learning approaches to accelerate numerical solvers, which provide faithful but computationally intensive simulations of the physical world.…
An algorithmic framework for the optimization of deep neural networks architectures and hyperparameters
Julie Keisler, El-Ghazali Talbi, Sandra Claudel +1
In this paper, we propose an algorithmic framework to automatically generate efficient deep neural networks and optimize their associated hyperparameters. The framework is based on…
A Visual Sensitivity Analysis for Parameter-Augmented Ensembles of Curves
Alejandro Ribes, Joachim Pouderoux, Bertrand Iooss
Engineers and computational scientists often study the behavior of their simulations by repeated solutions with variations in their parameters, which can be for instance boundary v…
Background Error Covariance Iterative Updating with Invariant Observation Measures for Data Assimilation
Sibo Cheng, Jean-Philippe Argaud, Bertrand Iooss +2
In order to leverage the information embedded in the background state and observations, covariance matrices modelling is a pivotal point in data assimilation algorithms. These matr…
Model Assisted Probability of Detection curves: New statistical tools and progressive methodology
Loïc Le Gratiet, Bertrand Iooss, Géraud Blatman +3
The Probability Of Detection (POD) curve is a standard tool in several industries to evaluate the performance of Non Destructive Testing (NDT) procedures for the detection of harmf…
Liquidity Management with Decreasing-returns-to-scale and Secured Credit Line
Erwan Pierre, Stéphane Villeneuve, Xavier Warin
This paper examines the dividend and investment policies of a cash constrained firm that has access to costly external funding. We depart from the literature by allowing the firm t…