Efficient learning of non-autoregressive graph variational autoencoders for molecular graph generation.

Kwon, Youngchun; Yoo, Jiho; Choi, Youn-Suk; Son, Won-Joon; Lee, Dongseon; Kang, Seokho

Kwon, Youngchun; Yoo, Jiho; Choi, Youn-Suk; Son, Won-Joon; Lee, Dongseon; Kang, Seokho.

Afiliación

Kwon Y; Samsung Advanced Institute of Technology, Samsung Electronics Co. Ltd., 130 Samsung-ro, Yeongtong-gu, Suwon, Republic of Korea.
Yoo J; Department of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, Republic of Korea.
Choi YS; Samsung Advanced Institute of Technology, Samsung Electronics Co. Ltd., 130 Samsung-ro, Yeongtong-gu, Suwon, Republic of Korea.
Son WJ; Samsung Advanced Institute of Technology, Samsung Electronics Co. Ltd., 130 Samsung-ro, Yeongtong-gu, Suwon, Republic of Korea.
Lee D; Samsung Advanced Institute of Technology, Samsung Electronics Co. Ltd., 130 Samsung-ro, Yeongtong-gu, Suwon, Republic of Korea.
Kang S; Samsung Advanced Institute of Technology, Samsung Electronics Co. Ltd., 130 Samsung-ro, Yeongtong-gu, Suwon, Republic of Korea.

J Cheminform ; 11(1): 70, 2019 Nov 21.

Article en En | MEDLINE | ID: mdl-33430985

Palabras clave

Deep learning; Graph neural network; Molecular graph; Variational autoencoder

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: J Cheminform Año: 2019 Tipo del documento: Article

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