Search Results for author: Kuhwan Jeong

Found 2 papers, 0 papers with code

Graph-Aware Transformer: Is Attention All Graphs Need?

no code implementations9 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.

Graph Classification Graph Generation

LATENT OPTIMIZATION VARIATIONAL AUTOENCODER FOR CONDITIONAL MOLECULAR GENERATION

no code implementations1 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.

Text Generation

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