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Machine Learning on Dynamic Graphs: A Survey on Applications

Machine Learning on Dynamic Graphs: A Survey on Applications

16 January 2024
Sanaz Hasanzadeh Fard
    AI4CE
ArXivPDFHTML

Papers citing "Machine Learning on Dynamic Graphs: A Survey on Applications"

47 / 47 papers shown
Title
MST-GAT: A Multimodal Spatial-Temporal Graph Attention Network for Time
  Series Anomaly Detection
MST-GAT: A Multimodal Spatial-Temporal Graph Attention Network for Time Series Anomaly Detection
Chaoyue Ding
Shiliang Sun
Jing Zhao
AI4TS
61
148
0
17 Oct 2023
Temporal Graph Benchmark for Machine Learning on Temporal Graphs
Temporal Graph Benchmark for Machine Learning on Temporal Graphs
Shenyang Huang
Farimah Poursafaei
Jacob Danovitch
Matthias Fey
Weihua Hu
Emanuele Rossi
J. Leskovec
Michael M. Bronstein
Guillaume Rabusseau
Reihaneh Rabbany
69
91
0
03 Jul 2023
ROLAND: Graph Learning Framework for Dynamic Graphs
ROLAND: Graph Learning Framework for Dynamic Graphs
Jiaxuan You
Tianyu Du
J. Leskovec
AI4CE
49
172
0
15 Aug 2022
Federated Graph Machine Learning: A Survey of Concepts, Techniques, and
  Applications
Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications
Xingbo Fu
Binchi Zhang
Yushun Dong
Chen Chen
Jundong Li
FedML
OOD
AI4CE
90
36
0
24 Jul 2022
Transformer for Graphs: An Overview from Architecture Perspective
Transformer for Graphs: An Overview from Architecture Perspective
Erxue Min
Runfa Chen
Yatao Bian
Tingyang Xu
Kangfei Zhao
Wenbing Huang
P. Zhao
Junzhou Huang
Sophia Ananiadou
Yu Rong
64
142
0
17 Feb 2022
Inductive Representation Learning in Temporal Networks via Mining
  Neighborhood and Community Influences
Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences
Meng Liu
Yong Liu
AI4TS
112
37
0
01 Oct 2021
Adversarial Attack for Uncertainty Estimation: Identifying Critical
  Regions in Neural Networks
Adversarial Attack for Uncertainty Estimation: Identifying Critical Regions in Neural Networks
Ismail Alarab
S. Prakoonwit
AAML
92
14
0
15 Jul 2021
Learning Dynamic Graph Representation of Brain Connectome with
  Spatio-Temporal Attention
Learning Dynamic Graph Representation of Brain Connectome with Spatio-Temporal Attention
Byung-Hoon Kim
Jong Chul Ye
Jae-Jin Kim
84
130
0
27 May 2021
Machine learning and deep learning
Machine learning and deep learning
Christian Janiesch
Patrick Zschech
Kai Heinrich
34
1,200
0
12 Apr 2021
An Energy-Efficient Quad-Camera Visual System for Autonomous Machines on
  FPGA Platform
An Energy-Efficient Quad-Camera Visual System for Autonomous Machines on FPGA Platform
Zishen Wan
Yuyang Zhang
A. Raychowdhury
Bo Yu
Haibin Ling
Shaoshan Liu
77
17
0
01 Apr 2021
Dynamic Network Embedding Survey
Dynamic Network Embedding Survey
Guotong Xue
Ming Zhong
Jianxin Li
Jia Chen
C. Zhai
Ruochen Kong
AI4TS
41
166
0
29 Mar 2021
PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive
  Learning
PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning
Yunbo Wang
Haixu Wu
Jianjin Zhang
Zhifeng Gao
Jianmin Wang
Philip S. Yu
Mingsheng Long
74
390
0
17 Mar 2021
TrackFormer: Multi-Object Tracking with Transformers
TrackFormer: Multi-Object Tracking with Transformers
Tim Meinhardt
A. Kirillov
Laura Leal-Taixe
Christoph Feichtenhofer
VOT
257
761
0
07 Jan 2021
A Survey on Embedding Dynamic Graphs
A Survey on Embedding Dynamic Graphs
Claudio D. T. Barros
Matheus R. F. Mendonça
A. Vieira
A. Ziviani
AI4TS
AI4CE
54
132
0
04 Jan 2021
Beyond Low-frequency Information in Graph Convolutional Networks
Beyond Low-frequency Information in Graph Convolutional Networks
Deyu Bo
Xiao Wang
C. Shi
Huawei Shen
GNN
165
586
0
04 Jan 2021
TransTrack: Multiple Object Tracking with Transformer
TransTrack: Multiple Object Tracking with Transformer
Pei Sun
Jinkun Cao
Yi Jiang
Rufeng Zhang
Enze Xie
Zehuan Yuan
Changhu Wang
Ping Luo
ViT
VOT
306
576
0
31 Dec 2020
Understanding graph embedding methods and their applications
Understanding graph embedding methods and their applications
Mengjia Xu
40
133
0
15 Dec 2020
A Survey on Heterogeneous Graph Embedding: Methods, Techniques,
  Applications and Sources
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources
Xiao Wang
Deyu Bo
C. Shi
Shaohua Fan
Yanfang Ye
Philip S. Yu
AI4TS
72
305
0
30 Nov 2020
Random Walks: A Review of Algorithms and Applications
Random Walks: A Review of Algorithms and Applications
Feng Xia
Jiaying Liu
Hansong Nie
Yonghao Fu
Liangtian Wan
X. Kong
53
188
0
09 Aug 2020
Deep Learning for Anomaly Detection: A Review
Deep Learning for Anomaly Detection: A Review
Guansong Pang
Chunhua Shen
LongBing Cao
Anton Van Den Hengel
156
920
0
06 Jul 2020
Simple and Deep Graph Convolutional Networks
Simple and Deep Graph Convolutional Networks
Ming Chen
Zhewei Wei
Zengfeng Huang
Bolin Ding
Yaliang Li
GNN
102
1,483
0
04 Jul 2020
Space-Time Correspondence as a Contrastive Random Walk
Space-Time Correspondence as a Contrastive Random Walk
Allan Jabri
Andrew Owens
Alexei A. Efros
SSL
OT
73
302
0
25 Jun 2020
Temporal Graph Networks for Deep Learning on Dynamic Graphs
Temporal Graph Networks for Deep Learning on Dynamic Graphs
Emanuele Rossi
B. Chamberlain
Fabrizio Frasca
D. Eynard
Federico Monti
M. Bronstein
AI4CE
140
643
0
18 Jun 2020
Machine Learning on Graphs: A Model and Comprehensive Taxonomy
Machine Learning on Graphs: A Model and Comprehensive Taxonomy
Ines Chami
Sami Abu-El-Haija
Bryan Perozzi
Christopher Ré
Kevin Patrick Murphy
85
289
0
07 May 2020
MOT20: A benchmark for multi object tracking in crowded scenes
MOT20: A benchmark for multi object tracking in crowded scenes
Patrick Dendorfer
Hamid Rezatofighi
Anton Milan
Javen Qinfeng Shi
Daniel Cremers
Ian Reid
Stefan Roth
Konrad Schindler
Laura Leal-Taixé
VOT
232
648
0
19 Mar 2020
Time-Varying Graph Learning with Constraints on Graph Temporal Variation
Time-Varying Graph Learning with Constraints on Graph Temporal Variation
Koki Yamada
Yuichi Tanaka
Antonio Ortega
AI4TS
56
43
0
10 Jan 2020
Dynamic Joint Variational Graph Autoencoders
Dynamic Joint Variational Graph Autoencoders
Sedigheh Mahdavi
Shima Khoshraftar
Aijun An
BDL
41
24
0
04 Oct 2019
Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional
  Networks for Financial Forensics
Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics
Mark Weber
Giacomo Domeniconi
Jie Chen
D. Weidele
Claudio Bellei
Tom Robinson
C. E. Leiserson
63
326
0
31 Jul 2019
Representation Learning for Dynamic Graphs: A Survey
Representation Learning for Dynamic Graphs: A Survey
Seyed Mehran Kazemi
Rishab Goel
Kshitij Jain
I. Kobyzev
Akshay Sethi
Peter Forsyth
Pascal Poupart
AI4TS
AI4CE
GNN
98
455
0
27 May 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
111
1,064
0
26 Feb 2019
Simplifying Graph Convolutional Networks
Simplifying Graph Convolutional Networks
Felix Wu
Tianyi Zhang
Amauri Souza
Christopher Fifty
Tao Yu
Kilian Q. Weinberger
GNN
205
3,168
0
19 Feb 2019
GCN-GAN: A Non-linear Temporal Link Prediction Model for Weighted
  Dynamic Networks
GCN-GAN: A Non-linear Temporal Link Prediction Model for Weighted Dynamic Networks
Kai Lei
Meng Qin
Bo Bai
Gong Zhang
Min Yang
38
168
0
26 Jan 2019
Deep Learning for Anomaly Detection: A Survey
Deep Learning for Anomaly Detection: A Survey
Raghavendra Chalapathy
Sanjay Chawla
AI4TS
138
1,491
0
10 Jan 2019
An Introduction to Deep Reinforcement Learning
An Introduction to Deep Reinforcement Learning
Vincent François-Lavet
Peter Henderson
Riashat Islam
Marc G. Bellemare
Joelle Pineau
OffRL
AI4CE
126
1,254
0
30 Nov 2018
dyngraph2vec: Capturing Network Dynamics using Dynamic Graph
  Representation Learning
dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning
Palash Goyal
Sujit Rokka Chhetri
A. Canedo
68
401
0
07 Sep 2018
Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic
  Thresholding
Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding
K. Hundman
V. Constantinou
Christopher Laporte
Ian Colwell
T. Söderström
AI4TS
97
1,247
0
13 Feb 2018
A Comprehensive Survey of Graph Embedding: Problems, Techniques and
  Applications
A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications
Hongyun Cai
V. Zheng
Kevin Chen-Chuan Chang
AI4TS
95
1,790
0
22 Sep 2017
Deep Reinforcement Learning that Matters
Deep Reinforcement Learning that Matters
Peter Henderson
Riashat Islam
Philip Bachman
Joelle Pineau
Doina Precup
David Meger
OffRL
116
1,946
0
19 Sep 2017
A Brief Survey of Deep Reinforcement Learning
A Brief Survey of Deep Reinforcement Learning
Kai Arulkumaran
M. Deisenroth
Miles Brundage
Anil Anthony Bharath
OffRL
120
2,805
0
19 Aug 2017
Time Series Anomaly Detection; Detection of anomalous drops with limited
  features and sparse examples in noisy highly periodic data
Time Series Anomaly Detection; Detection of anomalous drops with limited features and sparse examples in noisy highly periodic data
Dominique T. Shipmon
Jason M. Gurevitch
Paolo Piselli
Stephen T. Edwards
AI4TS
39
131
0
11 Aug 2017
Inductive Representation Learning on Large Graphs
Inductive Representation Learning on Large Graphs
William L. Hamilton
Z. Ying
J. Leskovec
454
15,179
0
07 Jun 2017
Graph Embedding Techniques, Applications, and Performance: A Survey
Graph Embedding Techniques, Applications, and Performance: A Survey
Palash Goyal
Emilio Ferrara
GNN
AI4TS
123
1,725
0
08 May 2017
Dynamic Graph Convolutional Networks
Dynamic Graph Convolutional Networks
Franco Manessi
A. Rozza
M. Manzo
GNN
79
373
0
20 Apr 2017
Deep Reinforcement Learning: An Overview
Deep Reinforcement Learning: An Overview
Yuxi Li
OffRL
VLM
152
1,530
0
25 Jan 2017
MOT16: A Benchmark for Multi-Object Tracking
MOT16: A Benchmark for Multi-Object Tracking
Anton Milan
Laura Leal-Taixe
Ian Reid
Stefan Roth
Konrad Schindler
VOT
142
1,796
0
02 Mar 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
673
9,290
0
06 Jun 2015
Multiple Object Tracking: A Literature Review
Multiple Object Tracking: A Literature Review
Wenhan Luo
Junliang Xing
Anton Milan
Xiaoqin Zhang
Wei Liu
Tae-Kyun Kim
VOT
95
808
0
26 Sep 2014
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