Zobrazeno 1 - 10
of 27 005
pro vyhledávání: '"Humbert AT"'
Autor:
Sanchez-Manzano, D., Humbert, V., Gutiérrez-Llorente, A., Zhang, D., Santamaria, J., Bibes, M., Iglesias, L., Villegas, Javier E.
Characterizing the dimensionality of the superconducting state in the infinite-layer (IL) nickelates is crucial to understand its nature. Most studies have addressed the problem by studying the anisotropy of the upper critical fields. Yet, the domina
Externí odkaz:
http://arxiv.org/abs/2410.14341
Autor:
Olson, Lauren, Humbert, Tom P., Fischer, Ricarda Anna-Lena, Westerveld, Bob, Kunneman, Florian, Guzmán, Emitzá
Many modern software applications present numerous ethical concerns due to conflicts between users' values and companies' priorities. Intersectional communities, those with multiple marginalized identities, are disproportionately affected by these et
Externí odkaz:
http://arxiv.org/abs/2410.08090
Neutron noise analysis is a predominant technique for fissile matter identification with passive methods. Quantifying the uncertainties associated with the estimated nuclear parameters is crucial for decision-making. A conservative uncertainty quanti
Externí odkaz:
http://arxiv.org/abs/2410.01522
Autor:
Humbert, Tristan
We show that, given a real or complex hyperbolic metric $g_0$ on a closed manifold $M$ of dimension $n\geq 3$, there exists a neighborhood $\mathcal U$ of $g_0$ in the space of negatively curved metrics such that for any $g\in \mathcal U$, the topolo
Externí odkaz:
http://arxiv.org/abs/2409.11197
Autor:
Humbert, Philippe
Methods used to infer nuclear parameters from neutron count statistics fall into two categories depending on whether they use moments or count number probabilities. As probabilities are in general more difficult to calculate, we are interested here i
Externí odkaz:
http://arxiv.org/abs/2408.04971
Autor:
Fournier, Étienne, Jeoffrion, Christine, Hmedan, Belal, Pellier, Damien, Fiorino, Humbert, Landry, Aurélie
Publikováno v:
Applied Ergonomics, Volume 119, September 2024, 104306
The 5.0 industry promotes collaborative robots (cobots). This research studies the impacts of cobot collaboration using an experimental setup. 120 participants realized a simple and a complex assembly task. 50% collaborated with another human (H/H) a
Externí odkaz:
http://arxiv.org/abs/2405.17910
We study conformal prediction in the one-shot federated learning setting. The main goal is to compute marginally and training-conditionally valid prediction sets, at the server-level, in only one round of communication between the agents and the serv
Externí odkaz:
http://arxiv.org/abs/2405.12567
Autor:
Wu, Yixin, He, Xinlei, Berrang, Pascal, Humbert, Mathias, Backes, Michael, Gong, Neil Zhenqiang, Zhang, Yang
A graph neural network (GNN) is a type of neural network that is specifically designed to process graph-structured data. Typically, GNNs can be implemented in two settings, including the transductive setting and the inductive setting. In the transduc
Externí odkaz:
http://arxiv.org/abs/2405.05784
YouTube introduced the Shorts video format in 2021, allowing users to upload short videos that are prominently displayed on its website and app. Despite having such a large visual footprint, there are no studies to date that have looked at the impact
Externí odkaz:
http://arxiv.org/abs/2403.00454
Sequential design is a highly active field of research in active learning which provides a general framework for the design of computer experiments to make the most of a low computational budget. It has been widely used to generate efficient surrogat
Externí odkaz:
http://arxiv.org/abs/2402.16520