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Publications

Affichage des publications 41 à 50 sur 948 au total

Machine Learning

Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees

Gaussian processes (GPs) are a Bayesian machine learning approach widely used to construct surrogate models for the uncertainty quantification of computer simulation codes in industrial applications. It provides both a mean predictor and an estimate…

Edgar Jaber, Vincent Blot, Nicolas Brunel, Vincent Chabridon, Emmanuel Remy, Bertrand Iooss, Didier Lucor, Mathilde Mougeot, Alessandro Leite

Computation

Sensitivity Analyses of a Multi-Physics Long-Term Clogging Model For Steam Generators

Long-term operation of nuclear steam generators can result in the occurrence of clogging, a deposition phenomenon that may increase the risk of mechanical and vibration loadings on tube bundles and internal structures as well as potentially…

Vincent Chabridon, Edgar Jaber, Emmanuel Remy, Michaël Baudin, Didier Lucor, Mathilde Mougeot, Bertrand Iooss

Numerical Analysis

Towards high-performance linear potential flow BEM solver with low-rank compressions

The interaction of water waves with floating bodies can be modelled with linear potential flow theory, numerically solved with the Boundary Element Method (BEM). This method requires the construction of dense matrices and the resolution of the…

Matthieu Ancellin, Pierre Marchand, Frédéric Dias

Energies -

or physical chemistry

Non-resonant inelastic X-ray scattering for discrimination of pigments

Inelastic X-ray scattering spectroscopy (IXS) has been used in many fields of solid state physics and theoretical chemistry as an accurate and quantitative probe of elementary excitations. We show that IXS spectra in the energy loss range below 100…

Lauren Dalecky, Francesco Sottile, Linda Hung, Laure Cazals, Agnès Desolneux, Aurélia Chevalier, Jean-Pascal Rueff, Loïc Bertrand

Physical Chemistry Chemical Physics -

Computer Vision and Pattern Recognition

On the Importance of Large Objects in CNN Based Object Detection Algorithms

Object detection models, a prominent class of machine learning algorithms, aim to identify and precisely locate objects in images or videos. However, this task might yield uneven performances sometimes caused by the objects sizes and the quality of…

Ahmed Ben Saad, Gabriele Facciolo, Axel Davy

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision -

Mathematics

Coherence-enhancing anisotropic diffusion filter for 3D high resolution reconstruction of P-wave velocity and density using full waveform inversion: application to a North Sea Ocean Bottom Cable dataset

Regularization is a central topic in the study of the solutions of ill-posed inverse problems. High resolution seismic imaging using full waveform inversion belongs to this category of problems. Regularization through anisotropic diffusion, a…

Ludovic Métivier, Romain Brossier, Alexandre Hoffmann, Jean-Marie Mirebeau, Giuseppe Provenzano, Alizia Tarayoun, Peng Yong

Geophysics -