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A Survey on Deep Graph Generation: Methods and Applications

A Survey on Deep Graph Generation: Methods and Applications

13 March 2022
Yanqiao Zhu
Yuanqi Du
Yinkai Wang
Yichen Xu
Jieyu Zhang
Qiang Liu
Shu Wu
    3DV
    GNN
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Papers citing "A Survey on Deep Graph Generation: Methods and Applications"

40 / 90 papers shown
Title
Graph Residual Flow for Molecular Graph Generation
Graph Residual Flow for Molecular Graph Generation
Shion Honda
Hirotaka Akita
Katsuhiko Ishiguro
Toshiki Nakanishi
Kenta Oono
36
42
0
30 Sep 2019
Cosmological N-body simulations: a challenge for scalable generative
  models
Cosmological N-body simulations: a challenge for scalable generative models
Nathanael Perraudin
Ankit Srivastava
Aurelien Lucchi
T. Kacprzak
Thomas Hofmann
Alexandre Réfrégier
26
33
0
15 Aug 2019
DeepNC: Deep Generative Network Completion
DeepNC: Deep Generative Network Completion
Cong Tran
Won-Yong Shin
Andreas Spitz
Michael Gertz
GNN
55
8
0
17 Jul 2019
Generative Modeling by Estimating Gradients of the Data Distribution
Generative Modeling by Estimating Gradients of the Data Distribution
Yang Song
Stefano Ermon
SyDa
DiffM
129
3,803
0
12 Jul 2019
A Two-Step Graph Convolutional Decoder for Molecule Generation
A Two-Step Graph Convolutional Decoder for Molecule Generation
Xavier Bresson
T. Laurent
46
61
0
08 Jun 2019
Scalable Generative Models for Graphs with Graph Attention Mechanism
Scalable Generative Models for Graphs with Graph Attention Mechanism
Wataru Kawai
Yusuke Mukuta
Tatsuya Harada
GNN
24
17
0
05 Jun 2019
MolecularRNN: Generating realistic molecular graphs with optimized
  properties
MolecularRNN: Generating realistic molecular graphs with optimized properties
Mariya Popova
Mykhailo Shvets
Junier Oliva
Olexandr Isayev
GNN
47
164
0
31 May 2019
Adversarial Learned Molecular Graph Inference and Generation
Adversarial Learned Molecular Graph Inference and Generation
Sebastian Polsterl
Christian Wachinger
GAN
88
7
0
24 May 2019
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs
Muhan Zhang
Shali Jiang
Zhicheng Cui
Roman Garnett
Yixin Chen
GNN
BDL
CML
53
199
0
24 Apr 2019
Mol-CycleGAN - a generative model for molecular optimization
Mol-CycleGAN - a generative model for molecular optimization
Łukasz Maziarka
Agnieszka Pocha
Jan Kaczmarczyk
Krzysztof Rataj
M. Warchoł
40
246
0
06 Feb 2019
Deep Learning on Graphs: A Survey
Deep Learning on Graphs: A Survey
Ziwei Zhang
Peng Cui
Wenwu Zhu
GNN
132
1,324
0
11 Dec 2018
Learning Multimodal Graph-to-Graph Translation for Molecular
  Optimization
Learning Multimodal Graph-to-Graph Translation for Molecular Optimization
Wengong Jin
Kevin Kaichuang Yang
Regina Barzilay
Tommi Jaakkola
65
226
0
03 Dec 2018
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation
  Models
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Daniil Polykovskiy
Alexander Zhebrak
Benjamín Sánchez-Lengeling
Sergey Golovanov
Oktai Tatanov
...
Simon Johansson
Hongming Chen
Sergey I. Nikolenko
Alán Aspuru-Guzik
Alex Zhavoronkov
ELM
225
644
0
29 Nov 2018
DEFactor: Differentiable Edge Factorization-based Probabilistic Graph
  Generation
DEFactor: Differentiable Edge Factorization-based Probabilistic Graph Generation
Rim Assouel
Mohamed Ahmed
Marwin H. S. Segler
Amir Saffari
Yoshua Bengio
47
54
0
24 Nov 2018
GuacaMol: Benchmarking Models for De Novo Molecular Design
GuacaMol: Benchmarking Models for De Novo Molecular Design
Nathan Brown
Marco Fiscato
Marwin H. S. Segler
Alain C. Vaucher
ELM
75
703
0
22 Nov 2018
Molecular Hypergraph Grammar with its Application to Molecular
  Optimization
Molecular Hypergraph Grammar with its Application to Molecular Optimization
Hiroshi Kajino
34
102
0
08 Sep 2018
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
245
895
0
07 Jun 2018
MolGAN: An implicit generative model for small molecular graphs
MolGAN: An implicit generative model for small molecular graphs
Nicola De Cao
Thomas Kipf
GNN
GAN
81
917
0
30 May 2018
Constrained Graph Variational Autoencoders for Molecule Design
Constrained Graph Variational Autoencoders for Molecule Design
Qi Liu
Miltiadis Allamanis
Marc Brockschmidt
Alexander L. Gaunt
BDL
50
453
0
23 May 2018
Generative Code Modeling with Graphs
Generative Code Modeling with Graphs
Marc Brockschmidt
Miltiadis Allamanis
Alexander L. Gaunt
Oleksandr Polozov
46
178
0
22 May 2018
Learning Deep Generative Models of Graphs
Learning Deep Generative Models of Graphs
Yujia Li
Oriol Vinyals
Chris Dyer
Razvan Pascanu
Peter W. Battaglia
GNN
AI4CE
95
659
0
08 Mar 2018
NetGAN: Generating Graphs via Random Walks
NetGAN: Generating Graphs via Random Walks
Aleksandar Bojchevski
Oleksandr Shchur
Daniel Zügner
Stephan Günnemann
GAN
GNN
79
361
0
02 Mar 2018
Link Prediction Based on Graph Neural Networks
Link Prediction Based on Graph Neural Networks
Muhan Zhang
Yixin Chen
GNN
38
1,912
0
27 Feb 2018
Syntax-Directed Variational Autoencoder for Structured Data
Syntax-Directed Variational Autoencoder for Structured Data
H. Dai
Yingtao Tian
Bo Dai
Steven Skiena
Le Song
63
324
0
24 Feb 2018
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
Jiaxuan You
Rex Ying
Xiang Ren
William L. Hamilton
J. Leskovec
GNN
BDL
75
840
0
24 Feb 2018
NeVAE: A Deep Generative Model for Molecular Graphs
NeVAE: A Deep Generative Model for Molecular Graphs
Bidisha Samanta
A. De
G. Jana
P. Chattaraj
Niloy Ganguly
Manuel Gomez Rodriguez
GNN
DRL
BDL
DiffM
46
214
0
14 Feb 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
284
1,358
0
12 Feb 2018
GraphVAE: Towards Generation of Small Graphs Using Variational
  Autoencoders
GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders
M. Simonovsky
N. Komodakis
GNN
BDL
71
842
0
09 Feb 2018
GraphGAN: Graph Representation Learning with Generative Adversarial Nets
GraphGAN: Graph Representation Learning with Generative Adversarial Nets
Hongwei Wang
Jia Wang
Jialin Wang
Miao Zhao
Weinan Zhang
Fuzheng Zhang
Xing Xie
Minyi Guo
GNN
GAN
47
623
0
22 Nov 2017
Learning to Represent Programs with Graphs
Learning to Represent Programs with Graphs
Miltiadis Allamanis
Marc Brockschmidt
Mahmoud Khademi
GNN
NAI
79
797
0
01 Nov 2017
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
278
19,902
0
30 Oct 2017
Representation Learning on Graphs: Methods and Applications
Representation Learning on Graphs: Methods and Applications
William L. Hamilton
Rex Ying
J. Leskovec
GNN
98
1,970
0
17 Sep 2017
Masked Autoregressive Flow for Density Estimation
Masked Autoregressive Flow for Density Estimation
George Papamakarios
Theo Pavlakou
Iain Murray
92
1,340
0
19 May 2017
The Kinetics Human Action Video Dataset
The Kinetics Human Action Video Dataset
W. Kay
João Carreira
Karen Simonyan
Brian Zhang
Chloe Hillier
...
Tim Green
T. Back
Apostol Natsev
Mustafa Suleyman
Andrew Zisserman
182
3,771
0
19 May 2017
Automatic chemical design using a data-driven continuous representation
  of molecules
Automatic chemical design using a data-driven continuous representation of molecules
Rafael Gómez-Bombarelli
Jennifer N. Wei
David Duvenaud
José Miguel Hernández-Lobato
Benjamín Sánchez-Lengeling
Dennis Sheberla
J. Aguilera-Iparraguirre
Timothy D. Hirzel
Ryan P. Adams
Alán Aspuru-Guzik
3DV
111
2,911
0
07 Oct 2016
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNN
SSL
393
28,795
0
09 Sep 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning
Faster Eigenvector Computation via Shift-and-Invert Preconditioning
Dan Garber
Laurent Dinh
Chi Jin
Jascha Narain Sohl-Dickstein
Samy Bengio
Praneeth Netrapalli
Aaron Sidford
149
3,670
0
26 May 2016
NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis
NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis
Amir Shahroudy
Jun Liu
T. Ng
G. Wang
166
2,470
0
11 Apr 2016
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Narain Sohl-Dickstein
Eric A. Weiss
Niru Maheswaranathan
Surya Ganguli
SyDa
DiffM
159
6,780
0
12 Mar 2015
Structured Generative Models of Natural Source Code
Structured Generative Models of Natural Source Code
Chris J. Maddison
Daniel Tarlow
47
171
0
02 Jan 2014
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