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Greatest papers with code

GraphEBM: Molecular Graph Generation with Energy-Based Models

31 Jan 2021divelab/DIG

We note that most existing approaches for molecular graph generation fail to guarantee the intrinsic property of permutation invariance, resulting in unexpected bias in generative models.

GRAPH GENERATION MOLECULAR GRAPH GENERATION

GraphNVP: An Invertible Flow Model for Generating Molecular Graphs

28 May 2019pfnet-research/chainer-chemistry

We propose GraphNVP, the first invertible, normalizing flow-based molecular graph generation model.

GRAPH GENERATION MOLECULAR GRAPH GENERATION

Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation

NeurIPS 2018 bowenliu16/rl_graph_generation

Generating novel graph structures that optimize given objectives while obeying some given underlying rules is fundamental for chemistry, biology and social science research.

GRAPH GENERATION MOLECULAR GRAPH GENERATION

MoFlow: An Invertible Flow Model for Generating Molecular Graphs

17 Jun 2020calvin-zcx/moflow

Generating molecular graphs with desired chemical properties driven by deep graph generative models provides a very promising way to accelerate drug discovery process.

DRUG DISCOVERY GRAPH GENERATION MOLECULAR GRAPH GENERATION

Reinforced Molecular Optimization with Neighborhood-Controlled Grammars

NeurIPS 2020 Zoesgithub/MNCE-RL

A major challenge in the pharmaceutical industry is to design novel molecules with specific desired properties, especially when the property evaluation is costly.

GRAPH GENERATION MOLECULAR GRAPH GENERATION