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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"

9 / 9 papers shown
Title
The Robustness of Structural Features in Species Interaction Networks
The Robustness of Structural Features in Species Interaction Networks
Sanaz Hasanzadeh Fard
Emily Dolson
36
0
0
24 Feb 2025
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
26
139
0
17 Oct 2023
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
85
37
0
01 Oct 2021
TrackFormer: Multi-Object Tracking with Transformers
TrackFormer: Multi-Object Tracking with Transformers
Tim Meinhardt
A. Kirillov
Laura Leal-Taixe
Christoph Feichtenhofer
VOT
218
742
0
07 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
89
556
0
04 Jan 2021
TransTrack: Multiple Object Tracking with Transformer
TransTrack: Multiple Object Tracking with Transformer
Pei Sun
Jinkun Cao
Yi-Xin Jiang
Rufeng Zhang
Enze Xie
Zehuan Yuan
Changhu Wang
Ping Luo
ViT
VOT
241
565
0
31 Dec 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
166
632
0
19 Mar 2020
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
80
1,230
0
30 Nov 2018
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
249
9,134
0
06 Jun 2015
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