Zobrazeno 1 - 10
of 1 335
pro vyhledávání: '"Matthis, P."'
Autor:
Boelts, Jan, Deistler, Michael, Gloeckler, Manuel, Tejero-Cantero, Álvaro, Lueckmann, Jan-Matthis, Moss, Guy, Steinbach, Peter, Moreau, Thomas, Muratore, Fabio, Linhart, Julia, Durkan, Conor, Vetter, Julius, Miller, Benjamin Kurt, Herold, Maternus, Ziaeemehr, Abolfazl, Pals, Matthijs, Gruner, Theo, Bischoff, Sebastian, Krouglova, Nastya, Gao, Richard, Lappalainen, Janne K., Mucsányi, Bálint, Pei, Felix, Schulz, Auguste, Stefanidi, Zinovia, Rodrigues, Pedro, Schröder, Cornelius, Zaid, Faried Abu, Beck, Jonas, Kapoor, Jaivardhan, Greenberg, David S., Gonçalves, Pedro J., Macke, Jakob H.
Scientists and engineers use simulators to model empirically observed phenomena. However, tuning the parameters of a simulator to ensure its outputs match observed data presents a significant challenge. Simulation-based inference (SBI) addresses this
Externí odkaz:
http://arxiv.org/abs/2411.17337
Autor:
Ma, Jiacheng, Thorade, Matthis
Cyclic frosting and defrosting operations constitute a common characteristic of air-source heat pumps in cold climates during winter. Simulation models that can capture simultaneous heat and mass transfer phenomena associated with frost/defrost behav
Externí odkaz:
http://arxiv.org/abs/2412.00017
Autor:
Kohlenberg, Leo, Horns, Leonard, Sadrieh, Frederic, Kiele, Nils, Clausen, Matthis, Ketterer, Konstantin, Navasardyan, Avetis, Czinczoll, Tamara, de Melo, Gerard, Herbrich, Ralf
Annotating large datasets can be challenging. However, crowd-sourcing is often expensive and can lack quality, especially for non-trivial tasks. We propose a method of using LLMs as few-shot learners for annotating data in a complex natural language
Externí odkaz:
http://arxiv.org/abs/2410.12470
Autor:
Ferreira, Fabio S., Ashburner, John, Bouzigues, Arabella, Suksasilp, Chatrin, Russell, Lucy L., Foster, Phoebe H., Ferry-Bolder, Eve, van Swieten, John C., Jiskoot, Lize C., Seelaar, Harro, Sanchez-Valle, Raquel, Laforce, Robert, Graff, Caroline, Galimberti, Daniela, Vandenberghe, Rik, de Mendonca, Alexandre, Tiraboschi, Pietro, Santana, Isabel, Gerhard, Alexander, Levin, Johannes, Sorbi, Sandro, Otto, Markus, Pasquier, Florence, Ducharme, Simon, Butler, Chris R., Ber, Isabelle Le, Finger, Elizabeth, Tartaglia, Maria C., Masellis, Mario, Rowe, James B., Synofzik, Matthis, Moreno, Fermin, Borroni, Barbara, Kaski, Samuel, Rohrer, Jonathan D., Mourao-Miranda, Janaina
In this study, we propose a novel approach to uncover subgroup-specific and subgroup-common latent factors addressing the challenges posed by the heterogeneity of neurological and mental disorders, which hinder disease understanding, treatment develo
Externí odkaz:
http://arxiv.org/abs/2410.07890
Publikováno v:
Medical Image Analysis, 2024, 97, pp.103270
Recently, federated learning has raised increasing interest in the medical image analysis field due to its ability to aggregate multi-center data with privacy-preserving properties. A large amount of federated training schemes have been published, wh
Externí odkaz:
http://arxiv.org/abs/2410.17265
Publikováno v:
Machine Learning and Knowledge Discovery in Databases. Research Track (ECML PKDD 2024), Sep 2024, Vilnius, Lithuania. pp.369-385
Empirical studies show that federated learning exhibits convergence issues in Non Independent and Identically Distributed (IID) setups. However, these studies only focus on label distribution shifts, or concept shifts (e.g. ambiguous tasks). In this
Externí odkaz:
http://arxiv.org/abs/2410.14693
Autor:
Imran, Ali, Varadharajan, Vivek Shankar, Braga, Rafael Gomes, Bouteiller, Yann, Abdalwhab, Abdalwhab Bakheet Mohamed, Di-Giacomo, Matthis, Mercader, Alexandra, Beltrame, Giovanni, St-Onge, David
Artistic performances involving robotic systems present unique technical challenges akin to those encountered in other field deployments. In this paper, we delve into the orchestration of robotic artistic performances, focusing on the complexities in
Externí odkaz:
http://arxiv.org/abs/2404.07795
The critical two-dimensional Brownian loop-soup is an infinite collection of non-interacting Brownian loops in a planar domain that possesses some combinatorial features related to the notion of indistinguishability of bosons. The properly renormaliz
Externí odkaz:
http://arxiv.org/abs/2403.07830
Publikováno v:
J. Chem. Phys. 161, 014507 (2024)
Little is known about the coupling of rotation and translation in dense systems. Here, we report results of confocal fluorescence microscopy where simultaneous recording of translational and rotational particle trajectories from a bidisperse colloida
Externí odkaz:
http://arxiv.org/abs/2401.01956
Autor:
Barron, Samantha V., Egger, Daniel J., Pelofske, Elijah, Bärtschi, Andreas, Eidenbenz, Stephan, Lehmkuehler, Matthis, Woerner, Stefan
Publikováno v:
Nature Computational Science (2024)
In this paper, we explore the impact of noise on quantum computing, particularly focusing on the challenges when sampling bit strings from noisy quantum computers as well as the implications for optimization and machine learning applications. We form
Externí odkaz:
http://arxiv.org/abs/2312.00733