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2408.04461
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Random Walk Diffusion for Efficient Large-Scale Graph Generation
8 August 2024
Tobias Bernecker
Ghalia Rehawi
Francesco Paolo Casale
Janine Knauer-Arloth
Annalisa Marsico
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Papers citing
"Random Walk Diffusion for Efficient Large-Scale Graph Generation"
33 / 33 papers shown
Learning Flexible Forward Trajectories for Masked Molecular Diffusion
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Taewon Kim
Sihyun Yu
SungSoo Ahn
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2
0
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Autoregressive Diffusion Model for Graph Generation
International Conference on Machine Learning (ICML), 2023
Lingkai Kong
Jiaming Cui
Haotian Sun
Yuchen Zhuang
B. Prakash
Chao Zhang
DiffM
255
101
0
17 Jul 2023
Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling
International Conference on Machine Learning (ICML), 2023
Xiaohui Chen
Jiaxing He
Xuhong Han
Liping Liu
DiffM
528
80
0
06 May 2023
Diffusion Models for Graphs Benefit From Discrete State Spaces
K. Haefeli
Karolis Martinkus
Nathanael Perraudin
Roger Wattenhofer
DiffM
495
72
0
04 Oct 2022
SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators
International Conference on Machine Learning (ICML), 2022
Karolis Martinkus
Andreas Loukas
Nathanael Perraudin
Roger Wattenhofer
295
103
0
04 Apr 2022
A Survey on Deep Graph Generation: Methods and Applications
LOG IN (LOG IN), 2022
Yanqiao Zhu
Yuanqi Du
Yinkai Wang
Yichen Xu
Jieyu Zhang
Qiang Liu
Shu Wu
3DV
GNN
494
75
0
13 Mar 2022
Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations
International Conference on Machine Learning (ICML), 2022
Jaehyeong Jo
Seul Lee
Sung Ju Hwang
DiffM
453
316
0
05 Feb 2022
On the Power of Edge Independent Graph Models
Neural Information Processing Systems (NeurIPS), 2021
Sudhanshu Chanpuriya
Cameron Musco
Konstantinos Sotiropoulos
Charalampos E. Tsourakakis
254
16
0
29 Oct 2021
Autoregressive Diffusion Models
Emiel Hoogeboom
Alexey A. Gritsenko
Jasmijn Bastings
Ben Poole
Rianne van den Berg
Tim Salimans
DiffM
628
215
0
05 Oct 2021
Structured Denoising Diffusion Models in Discrete State-Spaces
Jacob Austin
Daniel D. Johnson
Jonathan Ho
Daniel Tarlow
Rianne van den Berg
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07 Jul 2021
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions
Neural Information Processing Systems (NeurIPS), 2021
Emiel Hoogeboom
Didrik Nielsen
P. Jaini
Patrick Forré
Max Welling
DiffM
797
620
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10 Feb 2021
A Systematic Survey on Deep Generative Models for Graph Generation
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
Xiaojie Guo
Bo Pan
MedIm
586
193
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13 Jul 2020
Scalable Deep Generative Modeling for Sparse Graphs
H. Dai
Azade Nazi
Yujia Li
Bo Dai
Dale Schuurmans
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205
94
0
28 Jun 2020
Denoising Diffusion Probabilistic Models
Jonathan Ho
Ajay Jain
Pieter Abbeel
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28,926
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19 Jun 2020
Permutation Invariant Graph Generation via Score-Based Generative Modeling
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Chenhao Niu
Yang Song
Jiaming Song
Shengjia Zhao
Aditya Grover
Stefano Ermon
DiffM
320
346
0
02 Mar 2020
Decision-Making with Auto-Encoding Variational Bayes
Neural Information Processing Systems (NeurIPS), 2020
Romain Lopez
Pierre Boyeau
Nir Yosef
Michael I. Jordan
Jeffrey Regier
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17 Feb 2020
Efficient Graph Generation with Graph Recurrent Attention Networks
Neural Information Processing Systems (NeurIPS), 2019
Renjie Liao
Yujia Li
Yang Song
Shenlong Wang
C. Nash
William L. Hamilton
David Duvenaud
R. Urtasun
R. Zemel
GNN
432
394
0
02 Oct 2019
Classification Accuracy Score for Conditional Generative Models
Neural Information Processing Systems (NeurIPS), 2019
Suman V. Ravuri
Oriol Vinyals
EGVM
532
264
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26 May 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
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112,756
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11 Oct 2018
Graphite: Iterative Generative Modeling of Graphs
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Aaron Zweig
Stefano Ermon
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438
324
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28 Mar 2018
NetGAN: Generating Graphs via Random Walks
International Conference on Machine Learning (ICML), 2018
Aleksandar Bojchevski
Oleksandr Shchur
Daniel Zügner
Stephan Günnemann
GAN
GNN
493
400
0
02 Mar 2018
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
Jiaxuan You
Rex Ying
Xiang Ren
William L. Hamilton
J. Leskovec
GNN
BDL
460
975
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24 Feb 2018
GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders
M. Simonovsky
N. Komodakis
GNN
BDL
473
969
0
09 Feb 2018
graph2vec: Learning Distributed Representations of Graphs
A. Narayanan
Mahinthan Chandramohan
R. Venkatesan
Lihui Chen
Yang Liu
Shantanu Jaiswal
GNN
436
865
0
17 Jul 2017
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking
Aleksandar Bojchevski
Stephan Günnemann
BDL
744
751
0
12 Jul 2017
Attention Is All You Need
Neural Information Processing Systems (NeurIPS), 2017
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
8.3K
171,167
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12 Jun 2017
Variational Graph Auto-Encoders
Thomas Kipf
Max Welling
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640
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21 Nov 2016
Semi-Supervised Classification with Graph Convolutional Networks
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Max Welling
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node2vec: Scalable Feature Learning for Networks
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03 Jul 2016
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Philipp Fischer
Thomas Brox
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Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Narain Sohl-Dickstein
Eric A. Weiss
Niru Maheswaranathan
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12 Mar 2015
DeepWalk: Online Learning of Social Representations
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Rami Al-Rfou
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26 Mar 2014
A Deep and Tractable Density Estimator
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Iain Murray
Hugo Larochelle
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430
210
0
07 Oct 2013
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