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Graph U-Nets

Graph U-Nets

11 May 2019
Hongyang Gao
Shuiwang Ji
    AI4CE
    SSL
    SSeg
    GNN
ArXivPDFHTML

Papers citing "Graph U-Nets"

10 / 210 papers shown
Title
A Gentle Introduction to Deep Learning for Graphs
A Gentle Introduction to Deep Learning for Graphs
D. Bacciu
Federico Errica
Alessio Micheli
Marco Podda
AI4CE
GNN
51
277
0
29 Dec 2019
Deep Graph Similarity Learning: A Survey
Deep Graph Similarity Learning: A Survey
Guixiang Ma
Nesreen Ahmed
Theodore L. Willke
Philip S. Yu
GNN
21
77
0
25 Dec 2019
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph
  Representations
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
Ekagra Ranjan
Soumya Sanyal
Partha P. Talukdar
GNN
23
329
0
18 Nov 2019
GraphZoom: A multi-level spectral approach for accurate and scalable
  graph embedding
GraphZoom: A multi-level spectral approach for accurate and scalable graph embedding
Chenhui Deng
Zhiqiang Zhao
Yongyu Wang
Zhiru Zhang
Zhuo Feng
32
105
0
06 Oct 2019
Universal Graph Transformer Self-Attention Networks
Universal Graph Transformer Self-Attention Networks
Dai Quoc Nguyen
T. Nguyen
Dinh Q. Phung
ViT
34
63
0
26 Sep 2019
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
A. Pareja
Giacomo Domeniconi
Jie Chen
Tengfei Ma
Toyotaro Suzumura
H. Kanezashi
Tim Kaler
Tao B. Schardl
Charles E. Leisersen
GNN
52
1,040
0
26 Feb 2019
Graph Neural Networks: A Review of Methods and Applications
Graph Neural Networks: A Review of Methods and Applications
Jie Zhou
Ganqu Cui
Shengding Hu
Zhengyan Zhang
Cheng Yang
Zhiyuan Liu
Lifeng Wang
Changcheng Li
Maosong Sun
AI4CE
GNN
28
5,400
0
20 Dec 2018
Convolutional Neural Network Architectures for Signals Supported on
  Graphs
Convolutional Neural Network Architectures for Signals Supported on Graphs
Fernando Gama
A. Marques
G. Leus
Alejandro Ribeiro
134
285
0
01 May 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs
Geometric deep learning on graphs and manifolds using mixture model CNNs
Federico Monti
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
Jan Svoboda
M. Bronstein
GNN
260
1,811
0
25 Nov 2016
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
261
3,240
0
24 Nov 2016
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