Zobrazeno 1 - 10
of 4 655
pro vyhledávání: '"Guille, A."'
Autor:
Santiago, Guille Carrión
In this paper, we introduce a model category structure in the category of functors from a filtered poset to cochain complexes in which higher limits of functors that take values in $R$-modules can be computed by means of a fibrant replacement. We exp
Externí odkaz:
http://arxiv.org/abs/2407.14205
Conformal prediction methodologies have significantly advanced the quantification of uncertainties in predictive models. Yet, the construction of confidence regions for model parameters presents a notable challenge, often necessitating stringent assu
Externí odkaz:
http://arxiv.org/abs/2405.18601
We explore a novel methodology for constructing confidence regions for parameters of linear models, using predictions from any arbitrary predictor. Our framework requires minimal assumptions on the noise and can be extended to functions deviating fro
Externí odkaz:
http://arxiv.org/abs/2401.15254
We characterize cofibrant objects in the category of functors indexed in a filtered poset and we show that these objects are acyclic. As a consequence, we show that Mackey functors over posets are also acyclic, where we define this type of Mackey fun
Externí odkaz:
http://arxiv.org/abs/2312.13989
Autor:
Winder, Claire Guille-Biel
Publikováno v:
13th International Congress on Mathematical Education, International Commission on Mathematical Instruction, Jul 2016, Hambourg, Germany
We are interested in the learning of 6 to 7 years old children in implementations of a situation of reproduction of figure by folding presented in the first part of this article. In the second part we expose our problem as well as our hypothesis and
Externí odkaz:
http://arxiv.org/abs/2312.06730
Autor:
Guille-Escuret, Charles, Noël, Pierre-André, Mitliagkas, Ioannis, Vazquez, David, Monteiro, Joao
Improving the reliability of deployed machine learning systems often involves developing methods to detect out-of-distribution (OOD) inputs. However, existing research often narrowly focuses on samples from classes that are absent from the training s
Externí odkaz:
http://arxiv.org/abs/2308.11480
Understanding the optimization dynamics of neural networks is necessary for closing the gap between theory and practice. Stochastic first-order optimization algorithms are known to efficiently locate favorable minima in deep neural networks. This eff
Externí odkaz:
http://arxiv.org/abs/2306.11922
Let $h$ be a connective homology theory. We construct a functorial relative plus construction as a Bousfield localization functor in the category of maps of spaces. It allows us to associate to a pair $(X, H)$ consisting of a connected space $X$ and
Externí odkaz:
http://arxiv.org/abs/2302.06892
Autor:
Ninon Very, Clémence Boulet, Céline Gheeraert, Alexandre Berthier, Manuel Johanns, Mohamed Bou Saleh, Loïc Guille, Fabrice Bray, Jean-Marc Strub, Marie Bobowski-Gerard, Francesco P. Zummo, Emmanuelle Vallez, Olivier Molendi-Coste, Eloise Woitrain, Sarah Cianférani, David Montaigne, Line Carolle Ntandja-Wandji, Laurent Dubuquoy, Julie Dubois-Chevalier, Bart Staels, Philippe Lefebvre, Jérôme Eeckhoute
Publikováno v:
Cell Death and Disease, Vol 15, Iss 6, Pp 1-22 (2024)
Abstract Tissue injury causes activation of mesenchymal lineage cells into wound-repairing myofibroblasts (MFs), whose uncontrolled activity ultimately leads to fibrosis. Although this process is triggered by deep metabolic and transcriptional reprog
Externí odkaz:
https://doaj.org/article/7c469a228cd14e0cb8f4aa98dabc701e
Autor:
François Bertucci, Florence Lerebours, Michele Ceccarelli, Arnaud Guille, Najeeb Syed, Pascal Finetti, José Adélaïde, Steven Van Laere, Anthony Goncalves, Patrice Viens, Daniel Birnbaum, Emilie Mamessier, Céline Callens, Davide Bedognetti
Publikováno v:
Journal of Translational Medicine, Vol 22, Iss 1, Pp 1-12 (2024)
Abstract Background Inflammatory breast cancer (IBC) is the most pro-metastatic form of BC. Better understanding of its enigmatic pathophysiology is crucial. We report here the largest whole-exome sequencing (WES) study of clinical IBC samples. Metho
Externí odkaz:
https://doaj.org/article/d411209f682649f3b4011eb089a7cbba