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Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via
  Ranking

Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking

12 July 2017
Aleksandar Bojchevski
Stephan Günnemann
    BDL
ArXivPDFHTML

Papers citing "Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking"

50 / 140 papers shown
Title
On the Ability of Graph Neural Networks to Model Interactions Between
  Vertices
On the Ability of Graph Neural Networks to Model Interactions Between Vertices
Noam Razin
Tom Verbin
Nadav Cohen
23
10
0
29 Nov 2022
Graph Neural Networks for Breast Cancer Data Integration
Graph Neural Networks for Breast Cancer Data Integration
Teodora Reu
32
1
0
28 Nov 2022
BeGin: Extensive Benchmark Scenarios and An Easy-to-use Framework for
  Graph Continual Learning
BeGin: Extensive Benchmark Scenarios and An Easy-to-use Framework for Graph Continual Learning
Jihoon Ko
Shinhwan Kang
Taehyung Kwon
Heechan Moon
Kijung Shin
CLL
46
7
0
26 Nov 2022
Resisting Graph Adversarial Attack via Cooperative Homophilous
  Augmentation
Resisting Graph Adversarial Attack via Cooperative Homophilous Augmentation
Zhihao Zhu
Chenwang Wu
Mingyang Zhou
Hao Liao
DefuLian
Enhong Chen
AAML
11
4
0
15 Nov 2022
Online Cross-Layer Knowledge Distillation on Graph Neural Networks with
  Deep Supervision
Online Cross-Layer Knowledge Distillation on Graph Neural Networks with Deep Supervision
Jiongyu Guo
Defang Chen
Can Wang
22
3
0
25 Oct 2022
Towards Accurate Subgraph Similarity Computation via Neural Graph
  Pruning
Towards Accurate Subgraph Similarity Computation via Neural Graph Pruning
Linfeng Liu
Xuhong Han
Dawei Zhou
Liping Liu
38
5
0
19 Oct 2022
Linkless Link Prediction via Relational Distillation
Linkless Link Prediction via Relational Distillation
Zhichun Guo
William Shiao
Shichang Zhang
Yozen Liu
Nitesh Chawla
Neil Shah
Tong Zhao
32
41
0
11 Oct 2022
Metric Distribution to Vector: Constructing Data Representation via
  Broad-Scale Discrepancies
Metric Distribution to Vector: Constructing Data Representation via Broad-Scale Discrepancies
Xue Liu
Dan Sun
X. Cao
Hao Ye
Wei Wei
20
0
0
02 Oct 2022
Clustering for directed graphs using parametrized random walk diffusion
  kernels
Clustering for directed graphs using parametrized random walk diffusion kernels
Harry Sevi
Matthieu Jonckheere
Argyris Kalogeratos
23
2
0
01 Oct 2022
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP
  Initialization
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
Xiaotian Han
Tong Zhao
Yozen Liu
Xia Hu
Neil Shah
GNN
66
36
0
30 Sep 2022
Graph Soft-Contrastive Learning via Neighborhood Ranking
Graph Soft-Contrastive Learning via Neighborhood Ranking
Zhiyuan Ning
P. Wang
Pengyang Wang
Ziyue Qiao
Wei Fan
Denghui Zhang
Yi Du
Yuanchun Zhou
23
15
0
28 Sep 2022
FedEgo: Privacy-preserving Personalized Federated Graph Learning with
  Ego-graphs
FedEgo: Privacy-preserving Personalized Federated Graph Learning with Ego-graphs
Taolin Zhang
Chuan Chen
Yaomin Chang
Lin Shu
Zibin Zheng
FedML
31
14
0
29 Aug 2022
Local Intrinsic Dimensionality Measures for Graphs, with Applications to
  Graph Embeddings
Local Intrinsic Dimensionality Measures for Graphs, with Applications to Graph Embeddings
Milovs Savić
V. Kurbalija
Milovs Radovanović
18
1
0
25 Aug 2022
LTE4G: Long-Tail Experts for Graph Neural Networks
LTE4G: Long-Tail Experts for Graph Neural Networks
Sukwon Yun
Kibum Kim
Kanghoon Yoon
Chanyoung Park
40
40
0
22 Aug 2022
BiFeat: Supercharge GNN Training via Graph Feature Quantization
BiFeat: Supercharge GNN Training via Graph Feature Quantization
Yuxin Ma
Ping Gong
Jun Yi
Z. Yao
Cheng-rong Li
Yuxiong He
Feng Yan
GNN
21
6
0
29 Jul 2022
Task-Adaptive Few-shot Node Classification
Task-Adaptive Few-shot Node Classification
Song Wang
Kaize Ding
Chuxu Zhang
Chen Chen
Jundong Li
OffRL
36
48
0
23 Jun 2022
GOOD: A Graph Out-of-Distribution Benchmark
GOOD: A Graph Out-of-Distribution Benchmark
Shurui Gui
Xiner Li
Limei Wang
Shuiwang Ji
OOD
38
116
0
16 Jun 2022
COIN: Communication-Aware In-Memory Acceleration for Graph Convolutional
  Networks
COIN: Communication-Aware In-Memory Acceleration for Graph Convolutional Networks
Sumit K. Mandal
Gokul Krishnan
A. Alper Goksoy
Gopikrishnan R. Nair
Yu Cao
Ümit Y. Ogras
GNN
29
10
0
15 May 2022
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity
Yuexiang Xie
Zhen Wang
Dawei Gao
Daoyuan Chen
Liuyi Yao
Weirui Kuang
Yaliang Li
Bolin Ding
Jingren Zhou
FedML
34
88
0
11 Apr 2022
Supervised Graph Contrastive Learning for Few-shot Node Classification
Supervised Graph Contrastive Learning for Few-shot Node Classification
Zhen Tan
Kaize Ding
Ruocheng Guo
Huan Liu
OffRL
37
11
0
29 Mar 2022
Improved Dual Correlation Reduction Network
Improved Dual Correlation Reduction Network
Yue Liu
Sihang Zhou
Xinwang Liu
Wenxuan Tu
Xihong Yang
26
22
0
25 Feb 2022
Graph Lifelong Learning: A Survey
Graph Lifelong Learning: A Survey
F. Febrinanto
Feng Xia
Kristen Moore
Chandra Thapa
Charu C. Aggarwal
CLL
AI4CE
44
51
0
22 Feb 2022
Graph Masked Autoencoders with Transformers
Graph Masked Autoencoders with Transformers
Sixiao Zhang
Hongxu Chen
Haoran Yang
Xiangguo Sun
Philip S. Yu
Guandong Xu
21
18
0
17 Feb 2022
Confidence May Cheat: Self-Training on Graph Neural Networks under
  Distribution Shift
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift
Hongrui Liu
Binbin Hu
Xiao Wang
Chuan Shi
Qing Cui
Jun Zhou
97
55
0
27 Jan 2022
Partition-Based Active Learning for Graph Neural Networks
Partition-Based Active Learning for Graph Neural Networks
Jiaqi Ma
Ziqiao Ma
Joyce Chai
Qiaozhu Mei
24
15
0
23 Jan 2022
Overcoming Oversmoothness in Graph Convolutional Networks via Hybrid
  Scattering Networks
Overcoming Oversmoothness in Graph Convolutional Networks via Hybrid Scattering Networks
Frederik Wenkel
Yimeng Min
M. Hirn
Michael Perlmutter
Guy Wolf
GNN
29
21
0
22 Jan 2022
Informative Pseudo-Labeling for Graph Neural Networks with Few Labels
Informative Pseudo-Labeling for Graph Neural Networks with Few Labels
Yayong Li
Jie Yin
Ling-Hao Chen
27
33
0
20 Jan 2022
Sequential Recommendation via Stochastic Self-Attention
Sequential Recommendation via Stochastic Self-Attention
Ziwei Fan
Zhiwei Liu
Alice Wang
Zahra Nazari
Lei Zheng
Hao Peng
Philip S. Yu
AI4TS
33
138
0
16 Jan 2022
Block Modeling-Guided Graph Convolutional Neural Networks
Block Modeling-Guided Graph Convolutional Neural Networks
Dongxiao He
Chundong Liang
Huixin Liu
Ming-Chang Wen
Pengfei Jiao
Zhiyong Feng
GNN
31
65
0
27 Dec 2021
Bootstrap Equilibrium and Probabilistic Speaker Representation Learning
  for Self-supervised Speaker Verification
Bootstrap Equilibrium and Probabilistic Speaker Representation Learning for Self-supervised Speaker Verification
Sung Hwan Mun
Min Hyun Han
Dongjune Lee
Jihwan Kim
N. Kim
SSL
43
3
0
16 Dec 2021
Structure-Aware Label Smoothing for Graph Neural Networks
Structure-Aware Label Smoothing for Graph Neural Networks
Yiwei Wang
Yujun Cai
Keli Zhang
Wei Wang
Henghui Ding
Muhao Chen
Jing Tang
Bryan Hooi
34
3
0
01 Dec 2021
Optimizing Sparse Matrix Multiplications for Graph Neural Networks
Optimizing Sparse Matrix Multiplications for Graph Neural Networks
Shenghao Qiu
You Liang
Zheng Wang
GNN
28
18
0
30 Oct 2021
Robustness of Graph Neural Networks at Scale
Robustness of Graph Neural Networks at Scale
Simon Geisler
Tobias Schmidt
Hakan cSirin
Daniel Zügner
Aleksandar Bojchevski
Stephan Günnemann
AAML
30
126
0
26 Oct 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node
  Classification
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification
Maximilian Stadler
Bertrand Charpentier
Simon Geisler
Daniel Zügner
Stephan Günnemann
UQCV
BDL
46
81
0
26 Oct 2021
Self-supervised Contrastive Attributed Graph Clustering
Self-supervised Contrastive Attributed Graph Clustering
Wei Xia
Quanxue Gao
Ming Yang
Xinbo Gao
SSL
68
29
0
15 Oct 2021
Asymmetric Graph Representation Learning
Asymmetric Graph Representation Learning
Zhuo Tan
B. Liu
Guosheng Yin
24
1
0
14 Oct 2021
Adaptive Multi-layer Contrastive Graph Neural Networks
Adaptive Multi-layer Contrastive Graph Neural Networks
S. Shi
Pengfei Xie
Xu Luo
Kai Qiao
Linyuan Wang
Jian Chen
B. Yan
OOD
24
5
0
29 Sep 2021
CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning
CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning
Sarkar Snigdha Sarathi Das
Arzoo Katiyar
R. Passonneau
Rui Zhang
40
141
0
15 Sep 2021
Node Feature Kernels Increase Graph Convolutional Network Robustness
Node Feature Kernels Increase Graph Convolutional Network Robustness
M. Seddik
Changmin Wu
J. Lutzeyer
Michalis Vazirgiannis
AAML
32
8
0
04 Sep 2021
Unsupervised Domain-adaptive Hash for Networks
Unsupervised Domain-adaptive Hash for Networks
Tao He
Lianli Gao
Jingkuan Song
Yuan-Fang Li
23
1
0
20 Aug 2021
Semi-supervised Network Embedding with Differentiable Deep Quantisation
Semi-supervised Network Embedding with Differentiable Deep Quantisation
Tao He
Lianli Gao
Jingkuan Song
Yuan-Fang Li
37
5
0
20 Aug 2021
BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly
  Detection
BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly Detection
Yulin Zhu
Y. Lai
Kaifa Zhao
Xiapu Luo
Ming Yuan
Jian Ren
Kai Zhou
AAML
33
24
0
18 Jun 2021
Modeling Sequences as Distributions with Uncertainty for Sequential
  Recommendation
Modeling Sequences as Distributions with Uncertainty for Sequential Recommendation
Ziwei Fan
Zhiwei Liu
Lei Zheng
Shen Wang
Philip S. Yu
40
49
0
11 Jun 2021
Self-Supervised Graph Learning with Proximity-based Views and Channel
  Contrast
Self-Supervised Graph Learning with Proximity-based Views and Channel Contrast
Wei Zhuo
Guang Tan
SSL
19
0
0
07 Jun 2021
Maximizing Mutual Information Across Feature and Topology Views for
  Learning Graph Representations
Maximizing Mutual Information Across Feature and Topology Views for Learning Graph Representations
Xiaolong Fan
Maoguo Gong
Yue Wu
Hao Li
SSL
33
4
0
14 May 2021
NODE-SELECT: A Graph Neural Network Based On A Selective Propagation
  Technique
NODE-SELECT: A Graph Neural Network Based On A Selective Propagation Technique
Steph-Yves M. Louis
Alireza Nasiri
Fatima J. Rolland
Cameron Mitro
Jianjun Hu
79
9
0
17 Feb 2021
Large-Scale Representation Learning on Graphs via Bootstrapping
Large-Scale Representation Learning on Graphs via Bootstrapping
S. Thakoor
Corentin Tallec
M. G. Azar
Mehdi Azabou
Eva L. Dyer
Rémi Munos
Petar Velivcković
Michal Valko
SSL
29
218
0
12 Feb 2021
Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph
  Convolutional Neural Networks
Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks
Yujun Yan
Milad Hashemi
Kevin Swersky
Yaoqing Yang
Danai Koutra
41
249
0
12 Feb 2021
Understanding graph embedding methods and their applications
Understanding graph embedding methods and their applications
Mengjia Xu
26
129
0
15 Dec 2020
NCGNN: Node-Level Capsule Graph Neural Network for Semisupervised
  Classification
NCGNN: Node-Level Capsule Graph Neural Network for Semisupervised Classification
Rui Yang
Wenrui Dai
Chenglin Li
Junni Zou
H. Xiong
34
20
0
07 Dec 2020
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