Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Bonnet Florent"'
Autor:
Yagoubi, Mouadh, Danan, David, Leyli-abadi, Milad, Brunet, Jean-Patrick, Mazari, Jocelyn Ahmed, Bonnet, Florent, gmati, maroua, Farjallah, Asma, Cinnella, Paola, Gallinari, Patrick, Schoenauer, Marc
The integration of machine learning (ML) techniques for addressing intricate physics problems is increasingly recognized as a promising avenue for expediting simulations. However, assessing ML-derived physical models poses a significant challenge for
Externí odkaz:
http://arxiv.org/abs/2407.01641
Autor:
Yagoubi, Mouadh, Leyli-Abadi, Milad, Danan, David, Brunet, Jean-Patrick, Mazari, Jocelyn Ahmed, Bonnet, Florent, Farjallah, Asma, Schoenauer, Marc, Gallinari, Patrick
The use of machine learning (ML) techniques to solve complex physical problems has been considered recently as a promising approach. However, the evaluation of such learned physical models remains an important issue for industrial use. The aim of thi
Externí odkaz:
http://arxiv.org/abs/2403.01623
In this paper, we investigate the behavior of gradient descent algorithms in physics-informed machine learning methods like PINNs, which minimize residuals connected to partial differential equations (PDEs). Our key result is that the difficulty in t
Externí odkaz:
http://arxiv.org/abs/2310.05801
Autor:
Bonnet, Florent
The study of partial differential equations (PDE) through the framework of deep learning emerged a few years ago leading to the impressive approximations of simple dynamics. Graph neural networks (GNN) turned out to be very useful in those tasks by a
Externí odkaz:
http://arxiv.org/abs/2305.05469
Publikováno v:
36th Conference on Neural Information Processing Systems (NeurIPS 2022) Track on Datasets and Benchmarks
Surrogate models are necessary to optimize meaningful quantities in physical dynamics as their recursive numerical resolutions are often prohibitively expensive. It is mainly the case for fluid dynamics and the resolution of Navier-Stokes equations.
Externí odkaz:
http://arxiv.org/abs/2212.07564
Publikováno v:
ICLR 2022 Workshop on Geometrical and Topological Representation Learning
Recent progress in \emph{Geometric Deep Learning} (GDL) has shown its potential to provide powerful data-driven models. This gives momentum to explore new methods for learning physical systems governed by \emph{Partial Differential Equations} (PDEs)
Externí odkaz:
http://arxiv.org/abs/2206.14709
Autor:
Fascia Pascal, Adnot Jérôme, Fontaine Juliette, Massardier-Pilonchéry Amélie, Boibieux André, Josset Laurence, Nicolas Guibert, Oria Fatima, Nazare Julie-Anne, Chiarello Pierre, Samperiz Audrey, Antonin Bal, Prudent Mélanie, Simon Chantal, Dulce Alfaiate, Fassier Jean-Baptiste, Florence Morfin-Sherpa, Constance d'Aubarede, Brunel-Dalmas Florence, Lahousse Matthieu, Pitiot Virginie, Trabaud Mary-Anne, Gaillot-Durand Lucie, Bal Antonin, Lina Bruno, Trouillet-Assant Sophie, Gueyffier François, Perry Marielle, Gillet Myriam, Adèle Paul, Jean-Baptiste Fassier, Valette Martine, Bourgeois Gaëlle, Lozano Hélène, Kahina Saker, Alfaiate Dulce, Morfin Florence, Mary-Anne Trabaud, Rabilloud Muriel, Schlienger Isabelle, Narbey David, Durupt François, Makhloufi Djamila, Bruno Pozzetto, Paul Adèle, Caire Eurydice, Bergeret Alain, Godinot Matthieu, Escuret Vanessa, Bonnet Florent, Moll Frédéric, Guibert Nicolas, Gaymard Alexandre, Cotte Laurent, Sophie Trouillet-Assant, Muriel Rabilloud, Virginie Pitiot, Amélie Massardier-Pilonchery, Milon Marie-Paule, Charbotel Barbara, Carole Langlois-Jacques, Bruno Lina
Publikováno v:
Clinical Microbiology and Infection
Clinical Microbiology and Infection, 2021, 3p. ⟨10.1016/j.cmi.2021.01.003⟩
Clinical Microbiology and Infection, 2021, 3p. ⟨10.1016/j.cmi.2021.01.003⟩
We conducted a prospective study in healthcare workers (n=296) of the University Hospital of Lyon, France. Serum samples (n=296) collected six months after disease onset were tested using three commercial assays: the Wantai Ab assay detecting total a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6016c5d1b1eea4e7edd9376c3c04f4d6
https://doi.org/10.1016/j.cmi.2021.01.003
https://doi.org/10.1016/j.cmi.2021.01.003
Autor:
Bonnet, Florent1 florentbonnet@hotmail.com, Pavy, Bernard1, Beaudoin, Sylvie2, Dubousset, Jean2, Mitrofanoff, Marc1
Publikováno v:
Scandinavian Journal of Plastic & Reconstructive Surgery & Hand Surgery. Jun2007, Vol. 41 Issue 3, p143-145. 3p. 4 Color Photographs.
Autor:
Lemaire, Hermine, Amgarou, Khalil, Khalil, Roger Abou, Angelique, Jean-Claude, Bonnet, Florent, De Toro, Daniel, Carrel, Frederick, Giarmana, Olivier, Gmar, Mehdi, Menaa, Nabil, Menesguen, Yves, Normand, Stephane, Patoz, Audrey, Schoepff, Vincent, Talent, Philippe, Timi, Tebug
Publikováno v:
2013 3rd International Conference on Advancements in Nuclear Instrumentation, Measurement Methods & their Applications (ANIMMA); 2013, p1-5, 5p
Publikováno v:
Evaluation Journal of Australasia; March 2015, Vol. 15 Issue: 1 p28-37, 10p