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Scalable Deep Generative Modeling for Sparse Graphs

Scalable Deep Generative Modeling for Sparse Graphs

28 June 2020
H. Dai
Azade Nazi
Yujia Li
Bo Dai
Dale Schuurmans
    BDL
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Papers citing "Scalable Deep Generative Modeling for Sparse Graphs"

15 / 15 papers shown
Title
Continual Learning on Graphs: A Survey
Continual Learning on Graphs: A Survey
Zonggui Tian
Duanhao Zhang
Hong-Ning Dai
47
5
0
09 Feb 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 Alexander Rieck
30
3
0
27 Nov 2023
D4Explainer: In-Distribution GNN Explanations via Discrete Denoising
  Diffusion
D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion
Jialin Chen
Shirley Wu
Abhijit Gupta
Rex Ying
DiffM
42
4
0
30 Oct 2023
GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph
  Generation
GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation
Han Huang
Leilei Sun
Bowen Du
Yanjie Fu
Weifeng Lv
DiffM
32
42
0
04 Dec 2022
NVDiff: Graph Generation through the Diffusion of Node Vectors
NVDiff: Graph Generation through the Diffusion of Node Vectors
Xiaohui Chen
Yukun Li
Aonan Zhang
Liping Liu
DiffM
20
21
0
19 Nov 2022
Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders
Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders
Kiarash Zahirnia
Oliver Schulte
Parmis Naddaf
Ke Li
29
10
0
30 Oct 2022
GEMS: Scene Expansion using Generative Models of Graphs
GEMS: Scene Expansion using Generative Models of Graphs
Rishi G. Agarwal
Tirupati Saketh Chandra
Vaidehi Patil
Aniruddha Mahapatra
K. Kulkarni
Vishwa Vinay
30
4
0
08 Jul 2022
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
DAMNETS: A Deep Autoregressive Model for Generating Markovian Network
  Time Series
DAMNETS: A Deep Autoregressive Model for Generating Markovian Network Time Series
J. Clarkson
Mihai Cucuringu
Andrew Elliott
Gesine Reinert
AI4TS
21
2
0
28 Mar 2022
Gransformer: Transformer-based Graph Generation
Gransformer: Transformer-based Graph Generation
Ahmad Khajenezhad
Seyed Ali Osia
Mahmood Karimian
H. Beigy
22
2
0
25 Mar 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
AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment
  of Implicit Graph Generators
AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators
Wenkai Xu
Gesine Reinert
29
4
0
07 Mar 2022
Score-based Generative Modeling of Graphs via the System of Stochastic
  Differential Equations
Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations
Jaehyeong Jo
Seul Lee
Sung Ju Hwang
DiffM
22
210
0
05 Feb 2022
Order Matters: Probabilistic Modeling of Node Sequence for Graph
  Generation
Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation
Xiaohui Chen
Xu Han
Jiajing Hu
Francisco J. R. Ruiz
Liping Liu
BDL
24
34
0
11 Jun 2021
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
224
1,340
0
12 Feb 2018
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