2 papers
cs.LG2024
Pre-training of Molecular GNNs via Conditional Boltzmann Generator
Daiki Koge, Naoaki Ono, Shigehiko Kanaya
Learning representations of molecular structures using deep learning is a fundamental problem in molecular property prediction tasks. Molecules inherently exist in the real world a…
cs.LG2023
Variational Autoencoding Molecular Graphs with Denoising Diffusion Probabilistic Model
Daiki Koge, Naoaki Ono, Shigehiko Kanaya
In data-driven drug discovery, designing molecular descriptors is a very important task. Deep generative models such as variational autoencoders (VAEs) offer a potential solution b…