Zobrazeno 1 - 10
of 16 755
pro vyhledávání: '"Genest, A."'
Previous OOD detection systems only focus on the semantic gap between ID and OOD samples. Besides the semantic gap, we are faced with two additional gaps: the domain gap between source and target domains, and the class-imbalance gap between different
Externí odkaz:
http://arxiv.org/abs/2412.06284
Publikováno v:
Sustainable Energy, Grids and Networks, 38, 101334 (2024)
In this paper, we compare the effectiveness of a two-stage control strategy for the energy management system (EMS) of a grid-connected microgrid under uncertain solar irradiance and load demand using a real-world dataset from an island in Southeast A
Externí odkaz:
http://arxiv.org/abs/2409.19568
Publikováno v:
Proceedings of the American Mathematical Society (2025)
This paper provides the first explicit formula for the expectation of the product of two disjoint principal minors of a Wishart random matrix, solving a part of a broader problem put forth by Samuel S. Wilks in 1934 in the Annals of Mathematics. The
Externí odkaz:
http://arxiv.org/abs/2409.14512
Out-of-distribution (OOD) detection targets to detect and reject test samples with semantic shifts, to prevent models trained on in-distribution (ID) dataset from producing unreliable predictions. Existing works only extract the appearance features o
Externí odkaz:
http://arxiv.org/abs/2409.09953
Autor:
Herman, Daniel I., Walsh, Mathieu, Kreider, Molly Kate, Lordi, Noah, Tsao, Eugene J., Lind, Alexander J., Heyrich, Matthew, Combes, Joshua, Genest, Jérôme, Diddams, Scott A.
Laser spectroscopy and interferometry have provided an unparalleled view into the fundamental nature of matter and the universe through ultra-precise measurements of atomic transition frequencies and gravitational waves. Optical frequency combs have
Externí odkaz:
http://arxiv.org/abs/2408.16688
Decision Trees (DTs) constitute one of the major highly non-linear AI models, valued, e.g., for their efficiency on tabular data. Learning accurate DTs is, however, complicated, especially for oblique DTs, and does take a significant training time. F
Externí odkaz:
http://arxiv.org/abs/2408.09135
Autor:
Genest, Christian, Ouimet, Frédéric
This paper introduces a local linear smoother for regression surfaces on the simplex. The estimator solves a least-squares regression problem weighted by a locally adaptive Dirichlet kernel, ensuring excellent boundary properties. Asymptotic results
Externí odkaz:
http://arxiv.org/abs/2408.07209
The development of digital twins (DTs) for physical systems increasingly leverages artificial intelligence (AI), particularly for combining data from different sources or for creating computationally efficient, reduced-dimension models. Indeed, even
Externí odkaz:
http://arxiv.org/abs/2406.19670
NIRPS first light and early science: breaking the 1 m/s RV precision barrier at infrared wavelengths
Autor:
Artigau, Étienne, Bouchy, François, Doyon, René, Baron, Frédérique, Malo, Lison, Wildi, François, Pepe, Franceso, Cook, Neil J., Thibault, Simon, Reshetov, Vladimir, Dumusque, Xavier, Lovis, Christophe, Sosnowska, Danuta, Martins, Bruno L. Canto, De Medeiros, Jose Renan, Delfosse, Xavier, Santos, Nuno, Rebolo, Rafael, Abreu, Manuel, Allain, Guillaume, Allart, Romain, Auger, Hugues, Barros, Susana, Bazinet, Luc, Blind, Nicolas, Boisse, Isabelle, Bonfils, Xavier, Bourrier, Vincent, Bovay, Sébastien, Broeg, Christopher, Brousseau, Denis, Bruniquel, Vincent, Cabral, Alexandre, Cadieux, Charles, Carmona, Andres, Carteret, Yann, Challita, Zalpha, Chazelas, Bruno, Cloutier, Ryan, Coelho, João, Cointepas, Marion, Conod, Uriel, Cowan, Nicolas, Cristo, Eduardo, da Silva, João Gomes, Dauplaise, Laurie, Gomes, Roseane de Lima, Delgado-Mena, Elisa, Ehrenreich, David, Faria, João, Figueira, Pedro, Forveille, Thierry, Frensch, Yolanda, Gagné, Jonathan, Genest, Frédéric, Genolet, Ludovic, Hernández, Jonay I. González, Témich, Félix Gracia, Grieves, Nolan, Hernandez, Olivier, Hobson, Melissa J., Hoeijmakers, Jens, Kerley, Dan, Krishnamurthy, Vigneshwaran, Lafrenière, David, Lamontagne, Pierrot, Larue, Pierre, Leaf, Henry, Leão, Izan C., Lim, Olivia, Curto, Gaspare Lo, Martins, Allan M., Melo, Claudio, Messias, Yuri S., Mignon, Lucile, Moranta, Leslie, Mordasini, Christoph, Moulla, Khaled Al, Mounzer, Dany, L'Heureux, Alexandrine, Nari, Nicola, Nielsen, Louise, Osborn, Ares, Parc, Léna, Pasquini, Luca, Passegger, Vera M., Pelletier, Stefan, Peroux, Céline, Piaulet, Caroline, Plotnykov, Mykhaylo, Poulin-Girard, Anne-Sophie, Rasilla, José Luis, Saint-Antoine, Jonathan, Sarajlic, Mirsad, Segovia, Alex, Seidel, Julia, Ségransan, Damien, Silva, Ana Rita Costa, Srivastava, Avidaan, Stefanov, Atanas K., Mascareño, Alejandro Suárez, Sordet, Michael, Teixeira, Márcio A., Udry, Stéphane, Valencia, Diana, Vallée, Philippe, Vandal, Thomas, Vaulato, Valentina, Wade, Gregg, Wardenier, Joost P., Wehbé, Bachar, Weisserman, Drew, Wevers, Ivan, Zins, Gérard
The Near-InfraRed Planet Searcher or NIRPS is a precision radial velocity spectrograph developed through collaborative efforts among laboratories in Switzerland, Canada, Brazil, France, Portugal and Spain. NIRPS extends to the 0.98-1.8 $\mu$m domain
Externí odkaz:
http://arxiv.org/abs/2406.08304
Publikováno v:
Stat (2024), 13 (2), e706, 6 pp
In 1934, the American statistician Samuel S. Wilks derived remarkable formulas for the joint moments of embedded principal minors of sample covariance matrices in multivariate Gaussian populations, and he used them to compute the moments of sample st
Externí odkaz:
http://arxiv.org/abs/2403.06330