Zobrazeno 1 - 10
of 335
pro vyhledávání: '"Véry, P"'
The aviation industry is vital for global transportation but faces increasing pressure to reduce its environmental footprint, particularly CO2 emissions from ground operations such as taxiing. Single Engine Taxiing (SET) has emerged as a promising te
Externí odkaz:
http://arxiv.org/abs/2410.07727
Accurately estimating aircraft fuel flow is essential for evaluating new procedures, designing next-generation aircraft, and monitoring the environmental impact of current aviation practices. This paper investigates the generalization capabilities of
Externí odkaz:
http://arxiv.org/abs/2410.07717
Unsupervised Domain Adaptation (UDA) aims to bridge the gap between a source domain, where labelled data are available, and a target domain only represented with unlabelled data. If domain invariant representations have dramatically improved the adap
Externí odkaz:
http://arxiv.org/abs/2012.01843
Autor:
Adjoua, Olivier, Lagardère, Louis, Jolly, Luc-Henri, Durocher, Arnaud, Very, Thibaut, Dupays, Isabelle, Wang, Zhi, Inizan, Théo Jaffrelot, Célerse, Frédéric, Ren, Pengyu, Ponder, Jay W., Piquemal, Jean-Philip
Publikováno v:
Journal of Chemical Theory and Computation, 2021, 17, 4, 2034-2053
We present the extension of the Tinker-HP package (Lagard\`ere et al., Chem. Sci., 2018,9, 956-972) to the use of Graphics Processing Unit (GPU) cards to accelerate molecular dynamics simulations using polarizable many-body force fields. The new high
Externí odkaz:
http://arxiv.org/abs/2011.01207
Unsupervised Domain Adaptation (UDA) has attracted a lot of attention in the last ten years. The emergence of Domain Invariant Representations (IR) has improved drastically the transferability of representations from a labelled source domain to a new
Externí odkaz:
http://arxiv.org/abs/2006.13629
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Unsupervised Domain Adaptation aims to learn a model on a source domain with labeled data in order to perform well on unlabeled data of a target domain. Current approaches focus on learning \textit{Domain Invariant Representations}. It relies on the
Externí odkaz:
http://arxiv.org/abs/1907.12299
Learning representations which remain invariant to a nuisance factor has a great interest in Domain Adaptation, Transfer Learning, and Fair Machine Learning. Finding such representations becomes highly challenging in NLP tasks since the nuisance fact
Externí odkaz:
http://arxiv.org/abs/1907.12305
Publikováno v:
Stress Biology, Vol 3, Iss 1, Pp 1-15 (2023)
Abstract The availability in the soil of potassium (K+), a poorly mobile macronutrient required in large quantities for plant growth, is generally suboptimal for crop production in the absence of fertilization, making improvement of the ability of cr
Externí odkaz:
https://doaj.org/article/3b2d17d90731480bb0a499dbb0f00604
