Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Ilya Shenbin"'
Autor:
Kuzma Khrabrov, Ilya Shenbin, Alexander Ryabov, Artem Tsypin, Alexander Telepov, Anton Alekseev, Alexander Grishin, Pavel Strashnov, Petr Zhilyaev, Sergey Nikolenko, Artur Kadurin
Publikováno v:
Physical chemistry chemical physics : PCCP. 24(42)
Electronic wave function calculation is a fundamental task of computational quantum chemistry. Knowledge of the wave function parameters allows one to compute physical and chemical properties of molecules and materials. Unfortunately, it is infeasibl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a68a6dd8f24b4bb592cc5d8b4e7266d7
https://pubmed.ncbi.nlm.nih.gov/36279016
https://pubmed.ncbi.nlm.nih.gov/36279016
Autor:
Michael Vasilkovsky, Anton Alekseev, Valentin Malykh, Ilya Shenbin, Elena Tutubalina, Dmitriy Salikhov, Mikhail Stepnov, Andrey Chertok, Sergey Nikolenko
State of the art neural methods for open information extraction (OpenIE) usually extract triplets (or tuples) iteratively in an autoregressive or predicate-based manner in order not to produce duplicates. In this work, we propose a different approach
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::421e4f597a8d971f5f48cf6b13dfa3a5
http://arxiv.org/abs/2206.12514
http://arxiv.org/abs/2206.12514
Publikováno v:
WSDM
Recent research has shown the advantages of using autoencoders based on deep neural networks for collaborative filtering. In particular, the recently proposed Mult-VAE model, which used the multinomial likelihood variational autoencoders, has shown e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::177491a6c73cefe5ff2813020cb09385
http://arxiv.org/abs/1912.11160
http://arxiv.org/abs/1912.11160
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030373337
AIST
AIST
In this work we investigate the impact of encoding mechanisms used in neural aspect extraction models on the quality of the resulting aspects. We concentrate on the neural attention-based aspect extraction (ABAE) model and evaluate five different typ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fec56c8ae6c99a2da3f71397676ab5fe
https://doi.org/10.1007/978-3-030-37334-4_15
https://doi.org/10.1007/978-3-030-37334-4_15
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030157180
ECIR (2)
ECIR (2)
We propose a novel end-to-end Aspect-based Rating Prediction model (AspeRa) that estimates user rating based on review texts for the items and at the same time discovers coherent aspects of reviews that can be used to explain predictions or profile u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7a7559a44f5d6e95c390351663bc70e
https://doi.org/10.1007/978-3-030-15719-7_21
https://doi.org/10.1007/978-3-030-15719-7_21
Autor:
Liang, Shangsong1 (AUTHOR) liangshangsong@gmail.com, Pan, Zhou1 (AUTHOR) panzh8@mail2.sysu.edu.cn, liu, wei2 (AUTHOR) liuw259@mail.sysu.edu.cn, Yin, Jian2 (AUTHOR) issjyin@mail.sysu.edu.cn, de Rijke, Maarten3 (AUTHOR) m.derijke@uva.nl
Publikováno v:
ACM Computing Surveys. Oct2024, Vol. 56 Issue 10, p1-40. 40p.
Autor:
G. Silva, Miguel1 (AUTHOR) mmgsilva@ciencias.ulisboa.pt, C. Madeira, Sara2 (AUTHOR) sacmadeira@ciencias.ulisboa.pt, Henriques, Rui3 (AUTHOR) rmch@tecnico.ulisboa.pt
Publikováno v:
ACM Computing Surveys. Dec2024, Vol. 56 Issue 12, p1-32. 32p.
Autor:
COPPOLILLO, ERICA, MINICI, MARCO, RITACCO, ETTORE, CAROPRESE, LUCIANO, PISANI, FRANCESCO SERGIO, MANCO, GIUSEPPE
Publikováno v:
ACM Transactions on Intelligent Systems & Technology; Aug2024, Vol. 15 Issue 4, p1-27, 27p
Publikováno v:
ACM Transactions on Knowledge Discovery from Data; Feb2024, Vol. 18 Issue 2, p1-24, 24p
Publikováno v:
ACM Transactions on Intelligent Systems & Technology; Dec2023, Vol. 14 Issue 6, p1-24, 24p