Graph Convolutional Neural Networks for Molecule Generation

Abstract

In this talk, I will discuss a graph convolutional neural network architecture for the molecule generation task. The proposed approach consists of two steps. First, a graph ConvNet is used to auto-encode molecules in one-shot. Second, beam search is applied to the output of neural networks to produce a valid chemical solution. Numerical experiments demonstrate the performances of this learning system.

Xavier Bresson

Assoc. Professor of Computer Science

Xavier Bresson is Associate Professor in Computer Science at NTU, Singapore. He is a leading researcher in the field of Graph Deep Learning, a new framework that combines graph theory and deep learning techniques.