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of 41
pro vyhledávání: '"A. Aransa"'
Autor:
García-Martínez, Mercedes, Caglayan, Ozan, Aransa, Walid, Bardet, Adrien, Bougares, Fethi, Barrault, Loïc
This paper describes LIUM submissions to WMT17 News Translation Task for English-German, English-Turkish, English-Czech and English-Latvian language pairs. We train BPE-based attentive Neural Machine Translation systems with and without factored outp
Externí odkaz:
http://arxiv.org/abs/1707.04499
Autor:
Caglayan, Ozan, Aransa, Walid, Bardet, Adrien, García-Martínez, Mercedes, Bougares, Fethi, Barrault, Loïc, Masana, Marc, Herranz, Luis, van de Weijer, Joost
This paper describes the monomodal and multimodal Neural Machine Translation systems developed by LIUM and CVC for WMT17 Shared Task on Multimodal Translation. We mainly explored two multimodal architectures where either global visual features or con
Externí odkaz:
http://arxiv.org/abs/1707.04481
Autor:
Caglayan, Ozan, García-Martínez, Mercedes, Bardet, Adrien, Aransa, Walid, Bougares, Fethi, Barrault, Loïc
In this paper, we present nmtpy, a flexible Python toolkit based on Theano for training Neural Machine Translation and other neural sequence-to-sequence architectures. nmtpy decouples the specification of a network from the training and inference uti
Externí odkaz:
http://arxiv.org/abs/1706.00457
Publikováno v:
Machine Translation, 2020 Apr 01. 34(1), 1-20.
Externí odkaz:
https://www.jstor.org/stable/48740610
Autor:
Caglayan, Ozan, Aransa, Walid, Wang, Yaxing, Masana, Marc, García-Martínez, Mercedes, Bougares, Fethi, Barrault, Loïc, van de Weijer, Joost
This paper presents the systems developed by LIUM and CVC for the WMT16 Multimodal Machine Translation challenge. We explored various comparative methods, namely phrase-based systems and attentional recurrent neural networks models trained using mono
Externí odkaz:
http://arxiv.org/abs/1605.09186
Publikováno v:
ACS Organic & Inorganic Au. 3:109-119
Poly(ethylene terephthalate) (PET) is the most common polyester plastic in the packaging industry and a major source of environmental pollution due to its single use. Several enzymes, termed PET hydrolases, have been found to hydrolyze this polymer a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73ee1409b89ffc1d831d1613b1dce8c5
https://doi.org/10.1021/acsorginorgau.2c00054
https://doi.org/10.1021/acsorginorgau.2c00054
Publikováno v:
Rona Teknik Pertanian, Vol 11, Iss 2, Pp 38-49 (2018)
Abstrak. Artikel ini memaparkan hasil analisis kecenderungan hujan tahunan di wilayah UPT PSDA di Pasuruan. Data hujan harian dari 69 lokasi digunakan untuk analisis. Periode rekaman data dari tahun 1980 sampai dengan tahun 2015. Analisis statistik d
Externí odkaz:
https://doaj.org/article/c360a7fa7cb645f88f15bb729a7662fe
Akademický článek
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Publikováno v:
Revista de Investigación en Salud VIVE; ene-abr2024, Vol. 7 Issue 19, p194-206, 13p
Polyethylene terephthalate (PET) is the most common polyester plastic in the packaging industry, and a major source of environmental pollution due to its single use. Several enzymes, termed PET hydrolases (PETases), have been found to hydrolyze this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0768e1361bf97e41c829178b5fd62710
https://doi.org/10.26434/chemrxiv-2022-gx4xc
https://doi.org/10.26434/chemrxiv-2022-gx4xc