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. 2202.13800
  4. Cited By
Differential equation and probability inspired graph neural networks for latent variable learning

Differential equation and probability inspired graph neural networks for latent variable learning

28 February 2022
Zhuangwei Shi
ArXivPDFHTML

Papers citing "Differential equation and probability inspired graph neural networks for latent variable learning"

28 / 28 papers shown
Title
Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction
Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction
Zhuangwei Shi
Yang Hu
Guangliang Mo
Jianguo Wu
AIFin
54
20
0
06 Apr 2022
Bidirectional LSTM-CRF Attention-based Model for Chinese Word
  Segmentation
Bidirectional LSTM-CRF Attention-based Model for Chinese Word Segmentation
Chen Jin
Zhuangwei Shi
Weihua Li
Yanbu Guo
64
9
0
20 May 2021
Incorporating Transformer and LSTM to Kalman Filter with EM algorithm
  for state estimation
Incorporating Transformer and LSTM to Kalman Filter with EM algorithm for state estimation
Zhuang Shi
86
11
0
01 May 2021
Continuous Graph Neural Networks
Continuous Graph Neural Networks
Louis-Pascal Xhonneux
Meng Qu
Jian Tang
GNN
92
154
0
02 Dec 2019
What Can Neural Networks Reason About?
What Can Neural Networks Reason About?
Keyulu Xu
Jingling Li
Mozhi Zhang
S. Du
Ken-ichi Kawarabayashi
Stefanie Jegelka
NAI
AI4CE
68
245
0
30 May 2019
GMNN: Graph Markov Neural Networks
GMNN: Graph Markov Neural Networks
Meng Qu
Yoshua Bengio
Jian Tang
BDL
GNN
60
291
0
15 May 2019
Graph U-Nets
Graph U-Nets
Hongyang Gao
Shuiwang Ji
AI4CE
SSL
SSeg
GNN
129
1,086
0
11 May 2019
Graph Convolutional Networks with EigenPooling
Graph Convolutional Networks with EigenPooling
Yao Ma
Suhang Wang
Charu C. Aggarwal
Jiliang Tang
GNN
173
334
0
30 Apr 2019
Self-Attention Graph Pooling
Self-Attention Graph Pooling
Junhyun Lee
Inyeop Lee
Jaewoo Kang
GNN
172
1,119
0
17 Apr 2019
Simplifying Graph Convolutional Networks
Simplifying Graph Convolutional Networks
Felix Wu
Tianyi Zhang
Amauri Souza
Christopher Fifty
Tao Yu
Kilian Q. Weinberger
GNN
233
3,172
0
19 Feb 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language
  Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
VLM
SSL
SSeg
1.8K
94,770
0
11 Oct 2018
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
240
7,642
0
01 Oct 2018
Graph Convolutional Networks for Text Classification
Graph Convolutional Networks for Text Classification
Liang Yao
Chengsheng Mao
Yuan Luo
GNN
92
1,825
0
15 Sep 2018
Hierarchical Graph Representation Learning with Differentiable Pooling
Hierarchical Graph Representation Learning with Differentiable Pooling
Rex Ying
Jiaxuan You
Christopher Morris
Xiang Ren
William L. Hamilton
J. Leskovec
GNN
295
2,146
0
22 Jun 2018
Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
414
5,103
0
19 Jun 2018
Attention-based Graph Neural Network for Semi-supervised Learning
Attention-based Graph Neural Network for Semi-supervised Learning
K. K. Thekumparampil
Chong-Jun Wang
Sewoong Oh
Li Li
GNN
71
333
0
10 Mar 2018
Deeper Insights into Graph Convolutional Networks for Semi-Supervised
  Learning
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning
Qimai Li
Zhichao Han
Xiao-Ming Wu
GNN
SSL
184
2,826
0
22 Jan 2018
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
479
20,138
0
30 Oct 2017
Maximum Principle Based Algorithms for Deep Learning
Maximum Principle Based Algorithms for Deep Learning
Qianxiao Li
Long Chen
Cheng Tai
E. Weinan
99
223
0
26 Oct 2017
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
698
131,526
0
12 Jun 2017
Inductive Representation Learning on Large Graphs
Inductive Representation Learning on Large Graphs
William L. Hamilton
Z. Ying
J. Leskovec
509
15,232
0
07 Jun 2017
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
593
7,443
0
04 Apr 2017
Variational Graph Auto-Encoders
Variational Graph Auto-Encoders
Thomas Kipf
Max Welling
GNN
BDL
SSL
CML
151
3,585
0
21 Nov 2016
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNN
SSL
617
29,051
0
09 Sep 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.8K
150,039
0
22 Dec 2014
Sequence to Sequence Learning with Neural Networks
Sequence to Sequence Learning with Neural Networks
Ilya Sutskever
Oriol Vinyals
Quoc V. Le
AIMat
434
20,553
0
10 Sep 2014
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau
Kyunghyun Cho
Yoshua Bengio
AIMat
552
27,300
0
01 Sep 2014
DeepWalk: Online Learning of Social Representations
DeepWalk: Online Learning of Social Representations
Bryan Perozzi
Rami Al-Rfou
Steven Skiena
HAI
254
9,789
0
26 Mar 2014
1