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GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
v1v2v3 (latest)

GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models

24 February 2018
Jiaxuan You
Rex Ying
Xiang Ren
William L. Hamilton
J. Leskovec
    GNNBDL
ArXiv (abs)PDFHTML

Papers citing "GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models"

28 / 28 papers shown
Title
Evolving Hard Maximum Cut Instances for Quantum Approximate Optimization Algorithms
Evolving Hard Maximum Cut Instances for Quantum Approximate Optimization Algorithms
Shuaiqun Pan
Yash J. Patel
Aneta Neumann
Frank Neumann
Thomas Bäck
Hao Wang
151
0
0
30 Jan 2025
Mix-of-Granularity: Optimize the Chunking Granularity for Retrieval-Augmented Generation
Mix-of-Granularity: Optimize the Chunking Granularity for Retrieval-Augmented Generation
Zijie Zhong
Hanwen Liu
Xiaoya Cui
Xiaofan Zhang
Zengchang Qin
139
8
0
28 Jan 2025
Learning to generate feasible graphs using graph grammars
Learning to generate feasible graphs using graph grammars
Stefan Mautner
Rolf Backofen
Fabrizio Costa
82
0
0
10 Jan 2025
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
Song Wang
Xiaodong Yang
Rashidul Islam
Huiyuan Chen
Minghua Xu
Jundong Li
Yiwei Cai
OODD
260
3
0
07 Jan 2025
LLMs generate structurally realistic social networks but overestimate political homophily
LLMs generate structurally realistic social networks but overestimate political homophily
Serina Chang
Alicja Chaszczewicz
Emma Wang
Maya Josifovska
Emma Pierson
J. Leskovec
126
8
0
29 Aug 2024
Random Walk Diffusion for Efficient Large-Scale Graph Generation
Random Walk Diffusion for Efficient Large-Scale Graph Generation
Tobias Bernecker
Ghalia Rehawi
Francesco Paolo Casale
Janine Knauer-Arloth
Annalisa Marsico
72
1
0
08 Aug 2024
Multi-Type Point Cloud Autoencoder: A Complete Equivariant Embedding for Molecule Conformation and Pose
Multi-Type Point Cloud Autoencoder: A Complete Equivariant Embedding for Molecule Conformation and Pose
Michael Kilgour
Mark Tuckerman
Jutta Rogal
85
0
0
22 May 2024
Metric Space Magnitude for Evaluating the Diversity of Latent Representations
Metric Space Magnitude for Evaluating the Diversity of Latent Representations
K. Limbeck
R. Andreeva
Rik Sarkar
Bastian Rieck
164
4
0
27 Nov 2023
Categorical Normalizing Flows via Continuous Transformations
Categorical Normalizing Flows via Continuous Transformations
Phillip Lippe
E. Gavves
BDL
105
44
0
17 Jun 2020
EvoNet: A Neural Network for Predicting the Evolution of Dynamic Graphs
EvoNet: A Neural Network for Predicting the Evolution of Dynamic Graphs
Changmin Wu
Giannis Nikolentzos
Michalis Vazirgiannis
GNN
303
10
0
02 Mar 2020
Learning to Fix Build Errors with Graph2Diff Neural Networks
Learning to Fix Build Errors with Graph2Diff Neural Networks
Daniel Tarlow
Subhodeep Moitra
Andrew Rice
Zimin Chen
Pierre-Antoine Manzagol
Charles Sutton
E. Aftandilian
GNN
117
63
0
04 Nov 2019
Graphite: Iterative Generative Modeling of Graphs
Graphite: Iterative Generative Modeling of Graphs
Aditya Grover
Aaron Zweig
Stefano Ermon
BDL
110
303
0
28 Mar 2018
Learning Deep Generative Models of Graphs
Learning Deep Generative Models of Graphs
Yujia Li
Oriol Vinyals
Chris Dyer
Razvan Pascanu
Peter W. Battaglia
GNNAI4CE
203
662
0
08 Mar 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
115
329
0
24 Feb 2018
GraphVAE: Towards Generation of Small Graphs Using Variational
  Autoencoders
GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders
M. Simonovsky
N. Komodakis
GNNBDL
123
856
0
09 Feb 2018
Representation Learning on Graphs: Methods and Applications
Representation Learning on Graphs: Methods and Applications
William L. Hamilton
Rex Ying
J. Leskovec
GNN
196
1,980
0
17 Sep 2017
Molecular De Novo Design through Deep Reinforcement Learning
Molecular De Novo Design through Deep Reinforcement Learning
Marcus Olivecrona
T. Blaschke
Ola Engkvist
Hongming Chen
BDL
150
1,019
0
25 Apr 2017
Generating Focussed Molecule Libraries for Drug Discovery with Recurrent
  Neural Networks
Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks
Marwin H. S. Segler
T. Kogej
C. Tyrchan
M. Waller
96
97
0
05 Jan 2017
Variational Graph Auto-Encoders
Variational Graph Auto-Encoders
Thomas Kipf
Max Welling
GNNBDLSSLCML
155
3,595
0
21 Nov 2016
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
180
2,939
0
07 Oct 2016
WaveNet: A Generative Model for Raw Audio
WaveNet: A Generative Model for Raw Audio
Aaron van den Oord
Sander Dieleman
Heiga Zen
Karen Simonyan
Oriol Vinyals
Alex Graves
Nal Kalchbrenner
A. Senior
Koray Kavukcuoglu
DiffM
406
7,421
0
12 Sep 2016
Pixel Recurrent Neural Networks
Pixel Recurrent Neural Networks
Aaron van den Oord
Nal Kalchbrenner
Koray Kavukcuoglu
SSegGAN
486
2,579
0
25 Jan 2016
Sliced Wasserstein Kernels for Probability Distributions
Sliced Wasserstein Kernels for Probability Distributions
Soheil Kolouri
Yang Zou
Gustavo K. Rohde
60
161
0
10 Nov 2015
A note on the evaluation of generative models
A note on the evaluation of generative models
Lucas Theis
Aaron van den Oord
Matthias Bethge
EGVM
150
1,146
0
05 Nov 2015
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence
  Modeling
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Junyoung Chung
Çağlar Gülçehre
Kyunghyun Cho
Yoshua Bengio
607
12,745
0
11 Dec 2014
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
458
16,922
0
20 Dec 2013
Kronecker Graphs: An Approach to Modeling Networks
Kronecker Graphs: An Approach to Modeling Networks
J. Leskovec
Deepayan Chakrabarti
Jon M. Kleinberg
Christos Faloutsos
Zoubin Ghahramani
122
1,076
0
29 Dec 2008
Mixed membership stochastic blockmodels
Mixed membership stochastic blockmodels
E. Airoldi
David M. Blei
S. Fienberg
Eric Xing
511
2,122
0
30 May 2007
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