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A Two-Step Graph Convolutional Decoder for Molecule Generation

A Two-Step Graph Convolutional Decoder for Molecule Generation

8 June 2019
Xavier Bresson
T. Laurent
ArXivPDFHTML

Papers citing "A Two-Step Graph Convolutional Decoder for Molecule Generation"

18 / 18 papers shown
Title
GIN-Graph: A Generative Interpretation Network for Model-Level Explanation of Graph Neural Networks
Xiao Yue
Guangzhi Qu
Lige Gan
GAN
FAtt
AI4CE
63
0
0
08 Mar 2025
GraphGANFed: A Federated Generative Framework for Graph-Structured
  Molecules Towards Efficient Drug Discovery
GraphGANFed: A Federated Generative Framework for Graph-Structured Molecules Towards Efficient Drug Discovery
Daniel Manu
Jingjing Yao
Wuji Liu
Xiang Sun
FedML
35
6
0
11 Apr 2023
SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits
  of One-shot Graph Generators
SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators
Karolis Martinkus
Andreas Loukas
Nathanael Perraudin
Roger Wattenhofer
42
67
0
04 Apr 2022
A Survey on Deep Graph Generation: Methods and Applications
A Survey on Deep Graph Generation: Methods and Applications
Yanqiao Zhu
Yuanqi Du
Yinkai Wang
Yichen Xu
Jieyu Zhang
Qiang Liu
Shu Wu
3DV
GNN
31
67
0
13 Mar 2022
Top-N: Equivariant set and graph generation without exchangeability
Top-N: Equivariant set and graph generation without exchangeability
Clément Vignac
P. Frossard
BDL
71
34
0
05 Oct 2021
Edge but not Least: Cross-View Graph Pooling
Edge but not Least: Cross-View Graph Pooling
Xiaowei Zhou
Jie Yin
Ivor W. Tsang
42
2
0
24 Sep 2021
Geometric learning of the conformational dynamics of molecules using
  dynamic graph neural networks
Geometric learning of the conformational dynamics of molecules using dynamic graph neural networks
Michael Ashby
Jenna A. Bilbrey
25
4
0
24 Jun 2021
Graph Context Encoder: Graph Feature Inpainting for Graph Generation and
  Self-supervised Pretraining
Graph Context Encoder: Graph Feature Inpainting for Graph Generation and Self-supervised Pretraining
Oriel Frigo
Rémy Brossard
David Dehaene
37
1
0
18 Jun 2021
Brain Multigraph Prediction using Topology-Aware Adversarial Graph
  Neural Network
Brain Multigraph Prediction using Topology-Aware Adversarial Graph Neural Network
Alaa Bessadok
Mohamed Ali Mahjoub
I. Rekik
MedIm
AI4CE
18
16
0
06 May 2021
Topology-Aware Generative Adversarial Network for Joint Prediction of
  Multiple Brain Graphs from a Single Brain Graph
Topology-Aware Generative Adversarial Network for Joint Prediction of Multiple Brain Graphs from a Single Brain Graph
Alaa Bessadok
Mohamed Ali Mahjoub
I. Rekik
MedIm
13
12
0
23 Sep 2020
A Systematic Survey on Deep Generative Models for Graph Generation
A Systematic Survey on Deep Generative Models for Graph Generation
Xiaojie Guo
Liang Zhao
MedIm
44
147
0
13 Jul 2020
MoFlow: An Invertible Flow Model for Generating Molecular Graphs
MoFlow: An Invertible Flow Model for Generating Molecular Graphs
Chengxi Zang
Fei Wang
BDL
28
280
0
17 Jun 2020
A Survey of Deep Learning for Scientific Discovery
A Survey of Deep Learning for Scientific Discovery
M. Raghu
Erica Schmidt
OOD
AI4CE
40
120
0
26 Mar 2020
Graph Representation Learning via Graphical Mutual Information
  Maximization
Graph Representation Learning via Graphical Mutual Information Maximization
Zhen Peng
Wenbing Huang
Minnan Luo
Q. Zheng
Yu Rong
Tingyang Xu
Junzhou Huang
SSL
47
566
0
04 Feb 2020
Study of Deep Generative Models for Inorganic Chemical Compositions
Study of Deep Generative Models for Inorganic Chemical Compositions
Yoshihide Sawada
Koji Morikawa
Mikiya Fujii
GAN
20
13
0
25 Oct 2019
Graph Convolutional Policy Network for Goal-Directed Molecular Graph
  Generation
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Jiaxuan You
Bowen Liu
Rex Ying
Vijay S. Pande
J. Leskovec
GNN
206
885
0
07 Jun 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
230
1,340
0
12 Feb 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs
Geometric deep learning on graphs and manifolds using mixture model CNNs
Federico Monti
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
Jan Svoboda
M. Bronstein
GNN
260
1,811
0
25 Nov 2016
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