ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2103.07016
  4. Cited By
On the Equivalence Between Temporal and Static Graph Representations for
  Observational Predictions

On the Equivalence Between Temporal and Static Graph Representations for Observational Predictions

12 March 2021
Jianfei Gao
Bruno Ribeiro
ArXivPDFHTML

Papers citing "On the Equivalence Between Temporal and Static Graph Representations for Observational Predictions"

13 / 13 papers shown
Title
How Neural Networks Extrapolate: From Feedforward to Graph Neural
  Networks
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Keyulu Xu
Mozhi Zhang
Jingling Li
S. Du
Ken-ichi Kawarabayashi
Stefanie Jegelka
MLT
82
311
0
24 Sep 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
95
641
0
18 Jun 2020
Relational Pooling for Graph Representations
Relational Pooling for Graph Representations
R. Murphy
Balasubramaniam Srinivasan
Vinayak A. Rao
Bruno Ribeiro
GNN
73
259
0
06 Mar 2019
E-LSTM-D: A Deep Learning Framework for Dynamic Network Link Prediction
E-LSTM-D: A Deep Learning Framework for Dynamic Network Link Prediction
Jinyin Chen
Jian Zhang
Xuanheng Xu
Chenbo Fu
Dan Zhang
Qingpeng Zhang
Qi Xuan
55
142
0
22 Feb 2019
On the Universality of Invariant Networks
On the Universality of Invariant Networks
Haggai Maron
Ethan Fetaya
Nimrod Segol
Y. Lipman
OOD
98
238
0
27 Jan 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
33
168
0
26 Jan 2019
Streaming Graph Neural Networks
Streaming Graph Neural Networks
Yao Ma
Ziyi Guo
Zhaochun Ren
Eric Zhao
Jiliang Tang
Dawei Yin
GNN
52
238
0
24 Oct 2018
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
Christopher Morris
Martin Ritzert
Matthias Fey
William L. Hamilton
J. E. Lenssen
Gaurav Rattan
Martin Grohe
GNN
136
1,625
0
04 Oct 2018
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
173
7,554
0
01 Oct 2018
Dynamic Graph Convolutional Networks
Dynamic Graph Convolutional Networks
Franco Manessi
A. Rozza
M. Manzo
GNN
64
368
0
20 Apr 2017
Structured Sequence Modeling with Graph Convolutional Recurrent Networks
Structured Sequence Modeling with Graph Convolutional Recurrent Networks
Youngjoo Seo
M. Defferrard
P. Vandergheynst
Xavier Bresson
GNN
83
764
0
22 Dec 2016
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence
  Modeling
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Junyoung Chung
Çağlar Gülçehre
Kyunghyun Cho
Yoshua Bengio
293
12,662
0
11 Dec 2014
Identifiability of Causal Graphs using Functional Models
Identifiability of Causal Graphs using Functional Models
J. Peters
Joris Mooij
Dominik Janzing
Bernhard Schölkopf
78
154
0
14 Feb 2012
1