no code implementations • 19 Feb 2022 • Sanghyun Yoo, Ohyun Kwon, Hoshik Lee
For several decades, chemical knowledge has been published in written text, and there have been many attempts to make it accessible, for example, by transforming such natural language text to a structured format.
no code implementations • 1 Jan 2021 • Tae Gyoon Kang, Ho-Gyeong Kim, Min-Joong Lee, Jihyun Lee, Seongmin Ok, Hoshik Lee, Young Sang Choi
Transformers with soft attention have been widely adopted to various sequence-to-sequence tasks.
no code implementations • 1 Jan 2021 • Kisoo Kwon, Jung-Hyun Park, Kuhwan Jeong, Sunjae Lee, Hoshik Lee
Variational autoencoder (VAE) is a generation algorithm, consisting of an encoder and a decoder, and the latent variable from the encoder is used as the input of the decoder.
no code implementations • 9 Jun 2020 • Sanghyun Yoo, Young-Seok Kim, Kang Hyun Lee, Kuhwan Jeong, Junhwi Choi, Hoshik Lee, Young Sang Choi
To cover the broad range of graph-data applications including graph classification as well as graph generation, it is desirable to have a general and flexible model consisting of an encoder and a decoder that can handle graph data.