Zobrazeno 1 - 10
of 91 870
pro vyhledávání: '"Moreau, AS"'
Autor:
Tangui, Sophia, Hurand, Simon, Aljasmi, Rashed, Benmoumen, Ayoub, David, Marie-Laure, Moreau, Philippe, Morisset, Sophie, Célérier, Stéphane, Mauchamp, Vincent
Publikováno v:
Small (2024): 2406334
MXenes stand out from other 2D materials because they combine very good electrical conductivity with hydrophilicity, allowing cost-effective processing as thin films. Therefore, there is a high fundamental interest in unraveling the electronic transp
Externí odkaz:
http://arxiv.org/abs/2411.05461
Autor:
Jung, HyunJun, Li, Weihang, Wu, Shun-Cheng, Bittner, William, Brasch, Nikolas, Song, Jifei, Pérez-Pellitero, Eduardo, Zhang, Zhensong, Moreau, Arthur, Navab, Nassir, Busam, Benjamin
Traditionally, 3d indoor datasets have generally prioritized scale over ground-truth accuracy in order to obtain improved generalization. However, using these datasets to evaluate dense geometry tasks, such as depth rendering, can be problematic as t
Externí odkaz:
http://arxiv.org/abs/2410.22715
The present study investigates the behaviour of the far-field sound radiated by low Mach number tip clearance flow induced by placing a stationary cambered airfoil adjacent to a stationary wall. The tip clearance heights ranged from 14% to 30% of the
Externí odkaz:
http://arxiv.org/abs/2410.01310
Autor:
Henkel, Owen, Horne-Robinson, Hannah, Dyshel, Maria, Ch, Nabil, Moreau-Pernet, Baptiste, Abood, Ralph
This paper introduces AMMORE, a new dataset of 53,000 math open-response question-answer pairs from Rori, a learning platform used by students in several African countries and conducts two experiments to evaluate the use of large language models (LLM
Externí odkaz:
http://arxiv.org/abs/2409.17904
Autor:
de Moreau, Simon, Almehio, Yasser, Bursuc, Andrei, El-Idrissi, Hafid, Stanciulescu, Bogdan, Moutarde, Fabien
Nighttime camera-based depth estimation is a highly challenging task, especially for autonomous driving applications, where accurate depth perception is essential for ensuring safe navigation. We aim to improve the reliability of perception systems a
Externí odkaz:
http://arxiv.org/abs/2409.08031
Publikováno v:
The Journal of Chemical Thermodynamics Volume 150, 2020, 106210
The limited availability of accurate experimental data in wide ranges of pressure, temperature, and composition is the main constraining factor for the proper development and assessment of thermodynamic models and equations of state. In the particula
Externí odkaz:
http://arxiv.org/abs/2409.17164
Autor:
Lozano-Martín, Daniel, Vega-Maza, David, Moreau, Alejandro, Martín, M. Carmen, Tuma, Dirk, Segovia, José J.
Publikováno v:
The Journal of Chemical Thermodynamics Volume 158, 2021, 106434
This work aims to address the technical aspects related to the thermodynamic characterization of natural gas mixtures blended with hydrogen for the introduction of alternative energy sources within the Power-to-Gas framework. For that purpose, new ex
Externí odkaz:
http://arxiv.org/abs/2409.04094
Autor:
Segovia, José J., Lozano-Martín, Daniel, Tuma, Dirk, Moreau, Alejandro, Martín, M. Carmen, Vega-Maza, David
Publikováno v:
The Journal of Chemical Thermodynamics Volume 171, 2022, 106791
This work aims to address the technical concerns related to the thermodynamic characterization of gas mixtures blended with hydrogen for the implementation of hydrogen as a new energy vector. For this purpose, new experimental speed of sound measurem
Externí odkaz:
http://arxiv.org/abs/2409.03677
Publikováno v:
Renewable Energy Volume 198, 2022, Pages 1398-1429
The accurate knowledge of the thermophysical and thermodynamic properties of pure hydrogen and hydrogen mixtures plays an important role in the design and operation of many processes involved in hydrogen production, transport, storage, and use. These
Externí odkaz:
http://arxiv.org/abs/2409.03666
Optical training of large-scale Transformers and deep neural networks with direct feedback alignment
Autor:
Wang, Ziao, Müller, Kilian, Filipovich, Matthew, Launay, Julien, Ohana, Ruben, Pariente, Gustave, Mokaadi, Safa, Brossollet, Charles, Moreau, Fabien, Cappelli, Alessandro, Poli, Iacopo, Carron, Igor, Daudet, Laurent, Krzakala, Florent, Gigan, Sylvain
Modern machine learning relies nearly exclusively on dedicated electronic hardware accelerators. Photonic approaches, with low consumption and high operation speed, are increasingly considered for inference but, to date, remain mostly limited to rela
Externí odkaz:
http://arxiv.org/abs/2409.12965