Feb. 20, 2024, 5:43 a.m. | Yasuhiro Yoshikai, Tadahaya Mizuno, Shumpei Nemoto, Hiroyuki Kusuhara

cs.LG updates on arXiv.org arxiv.org

arXiv:2402.11950v1 Announce Type: cross
Abstract: Recently, molecule generation using deep learning has been actively investigated in drug discovery. In this field, Transformer and VAE are widely used as powerful models, but they are rarely used in combination due to structural and performance mismatch of them. This study proposes a model that combines these two models through structural and parameter optimization in handling diverse molecules. The proposed model shows comparable performance to existing models in generating molecules, and showed by far …

abstract arxiv combination cs.lg deep learning discovery drug discovery generative novel performance physics.chem-ph q-bio.bm study them transformer type vae

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Senior ML Engineer

@ Carousell Group | Ho Chi Minh City, Vietnam

Data and Insight Analyst

@ Cotiviti | Remote, United States