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Learning Graph Structure from Convolutional Mixtures

Learning Graph Structure from Convolutional Mixtures

19 May 2022
Max Wasserman
Saurabh Sihag
Gonzalo Mateos
Alejandro Ribeiro
    GNN
    CML
    BDL
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Papers citing "Learning Graph Structure from Convolutional Mixtures"

28 / 28 papers shown
Title
Deconvolutional Networks on Graph Data
Deconvolutional Networks on Graph Data
Jia Li
Jiajin Li
Yang Liu
Jianwei Yu
Yueting Li
Hongtao Cheng
GNN
48
21
0
29 Oct 2021
Learning to Learn Graph Topologies
Learning to Learn Graph Topologies
Xingyue Pu
Tianyue Cao
Xiaoyun Zhang
Xiaowen Dong
Siheng Chen
46
41
0
19 Oct 2021
Graph Neural Networks with Learnable Structural and Positional
  Representations
Graph Neural Networks with Learnable Structural and Positional Representations
Vijay Prakash Dwivedi
Anh Tuan Luu
T. Laurent
Yoshua Bengio
Xavier Bresson
GNN
256
326
0
15 Oct 2021
From Local Structures to Size Generalization in Graph Neural Networks
From Local Structures to Size Generalization in Graph Neural Networks
Gilad Yehudai
Ethan Fetaya
E. Meirom
Gal Chechik
Haggai Maron
GNN
AI4CE
204
135
0
17 Oct 2020
Data Augmentation for Graph Neural Networks
Data Augmentation for Graph Neural Networks
Tong Zhao
Yozen Liu
Leonardo Neves
Oliver J. Woodford
Meng Jiang
Neil Shah
GNN
114
414
0
11 Jun 2020
Pointer Graph Networks
Pointer Graph Networks
Petar Velivcković
Lars Buesing
Matthew Overlan
Razvan Pascanu
Oriol Vinyals
Charles Blundell
GNN
94
62
0
11 Jun 2020
Graphs, Convolutions, and Neural Networks: From Graph Filters to Graph
  Neural Networks
Graphs, Convolutions, and Neural Networks: From Graph Filters to Graph Neural Networks
Fernando Gama
Elvin Isufi
G. Leus
Alejandro Ribeiro
GNN
82
155
0
08 Mar 2020
Differentiable Graph Module (DGM) for Graph Convolutional Networks
Differentiable Graph Module (DGM) for Graph Convolutional Networks
Anees Kazi
Luca Cosmo
Seyed-Ahmad Ahmadi
Nassir Navab
M. Bronstein
GNN
MedIm
59
130
0
11 Feb 2020
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal
  and Image Processing
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing
V. Monga
Yuelong Li
Yonina C. Eldar
92
1,020
0
22 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
406
42,393
0
03 Dec 2019
Efficient Graph Generation with Graph Recurrent Attention Networks
Efficient Graph Generation with Graph Recurrent Attention Networks
Renjie Liao
Yujia Li
Yang Song
Shenlong Wang
C. Nash
William L. Hamilton
David Duvenaud
R. Urtasun
R. Zemel
GNN
123
334
0
02 Oct 2019
GLAD: Learning Sparse Graph Recovery
GLAD: Learning Sparse Graph Recovery
H. Shrivastava
Xinshi Chen
Binghong Chen
Guanghui Lan
Srinvas Aluru
Han Liu
Le Song
CML
33
36
0
01 Jun 2019
Stability Properties of Graph Neural Networks
Stability Properties of Graph Neural Networks
Fernando Gama
Joan Bruna
Alejandro Ribeiro
63
232
0
11 May 2019
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
230
7,638
0
01 Oct 2018
Learning graphs from data: A signal representation perspective
Learning graphs from data: A signal representation perspective
Xiaowen Dong
D. Thanou
Michael G. Rabbat
P. Frossard
91
381
0
03 Jun 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
184
661
0
08 Mar 2018
Link Prediction Based on Graph Neural Networks
Link Prediction Based on Graph Neural Networks
Muhan Zhang
Yixin Chen
GNN
79
1,929
0
27 Feb 2018
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and
  Max-Det Matrix Completion
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion
Richard Y. Zhang
Salar Fattahi
Somayeh Sojoudi
53
30
0
14 Feb 2018
Dynamic Graph CNN for Learning on Point Clouds
Dynamic Graph CNN for Learning on Point Clouds
Yue Wang
Yongbin Sun
Ziwei Liu
Sanjay E. Sarma
M. Bronstein
Justin Solomon
GNN
3DPC
255
6,132
0
24 Jan 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
77
624
0
22 Nov 2017
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
778
3,282
0
24 Nov 2016
Variational Graph Auto-Encoders
Variational Graph Auto-Encoders
Thomas Kipf
Max Welling
GNN
BDL
SSL
CML
140
3,577
0
21 Nov 2016
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNN
SSL
593
28,999
0
09 Sep 2016
Structure Learning in Graphical Modeling
Structure Learning in Graphical Modeling
Mathias Drton
Marloes H. Maathuis
CML
77
249
0
07 Jun 2016
How to learn a graph from smooth signals
How to learn a graph from smooth signals
Vassilis Kalofolias
67
515
0
11 Jan 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.7K
150,006
0
22 Dec 2014
Estimating Diffusion Network Structures: Recovery Conditions, Sample
  Complexity & Soft-thresholding Algorithm
Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm
Hadi Daneshmand
Manuel Gomez Rodriguez
Le Song
Bernhard Schölkopf
TPM
52
120
0
12 May 2014
Learning efficient sparse and low rank models
Learning efficient sparse and low rank models
Pablo Sprechmann
A. Bronstein
Guillermo Sapiro
150
192
0
14 Dec 2012
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