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An open unified deep graph learning framework for discovering drug leads

An open unified deep graph learning framework for discovering drug leads

6 December 2022
Yueming Yin
Haifeng Hu
Zhen Yang
Jitao Yang
Chun Jimmie Ye
Jiansheng Wu
W. Goh
ArXivPDFHTML

Papers citing "An open unified deep graph learning framework for discovering drug leads"

21 / 21 papers shown
Title
Synergy and Symmetry in Deep Learning: Interactions between the Data,
  Model, and Inference Algorithm
Synergy and Symmetry in Deep Learning: Interactions between the Data, Model, and Inference Algorithm
Lechao Xiao
Jeffrey Pennington
56
10
0
11 Jul 2022
A Deep Generative Model for Molecule Optimization via One Fragment
  Modification
A Deep Generative Model for Molecule Optimization via One Fragment Modification
Ziqi Chen
Martin Renqiang Min
Srinivasan Parthasarathy
Xia Ning
44
67
0
08 Dec 2020
Optimizing Molecules using Efficient Queries from Property Evaluations
Optimizing Molecules using Efficient Queries from Property Evaluations
Samuel C. Hoffman
Vijil Chenthamarakshan
Kahini Wadhawan
Pin-Yu Chen
Payel Das
64
70
0
03 Nov 2020
Metric-Learning-Assisted Domain Adaptation
Metric-Learning-Assisted Domain Adaptation
Yueming Yin
Zhen Yang
Haifeng Hu
Xiaofu Wu
OOD
26
11
0
23 Apr 2020
CORE: Automatic Molecule Optimization Using Copy & Refine Strategy
CORE: Automatic Molecule Optimization Using Copy & Refine Strategy
Tianfan Fu
Cao Xiao
Jimeng Sun
94
65
0
23 Nov 2019
Graph Residual Flow for Molecular Graph Generation
Graph Residual Flow for Molecular Graph Generation
Shion Honda
Hirotaka Akita
Katsuhiko Ishiguro
Toshiki Nakanishi
Kenta Oono
52
42
0
30 Sep 2019
Strategies for Pre-training Graph Neural Networks
Strategies for Pre-training Graph Neural Networks
Weihua Hu
Bowen Liu
Joseph Gomes
Marinka Zitnik
Percy Liang
Vijay S. Pande
J. Leskovec
SSL
AI4CE
86
1,377
0
29 May 2019
GraphNVP: An Invertible Flow Model for Generating Molecular Graphs
GraphNVP: An Invertible Flow Model for Generating Molecular Graphs
Kaushalya Madhawa
Katushiko Ishiguro
Kosuke Nakago
Motoki Abe
BDL
96
190
0
28 May 2019
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
175
7,554
0
01 Oct 2018
Learning Deep Generative Models of Graphs
Learning Deep Generative Models of Graphs
Yujia Li
Oriol Vinyals
Chris Dyer
Razvan Pascanu
Peter W. Battaglia
GNN
AI4CE
136
659
0
08 Mar 2018
Syntax-Directed Variational Autoencoder for Structured Data
Syntax-Directed Variational Autoencoder for Structured Data
H. Dai
Yingtao Tian
Bo Dai
Steven Skiena
Le Song
77
325
0
24 Feb 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
296
1,358
0
12 Feb 2018
GraphVAE: Towards Generation of Small Graphs Using Variational
  Autoencoders
GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders
M. Simonovsky
N. Komodakis
GNN
BDL
92
842
0
09 Feb 2018
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
348
19,991
0
30 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
490
129,831
0
12 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
300
7,388
0
04 Apr 2017
Grammar Variational Autoencoder
Grammar Variational Autoencoder
Matt J. Kusner
Brooks Paige
José Miguel Hernández-Lobato
BDL
DRL
66
838
0
06 Mar 2017
Automatic chemical design using a data-driven continuous representation
  of molecules
Automatic chemical design using a data-driven continuous representation of molecules
Rafael Gómez-Bombarelli
Jennifer N. Wei
David Duvenaud
José Miguel Hernández-Lobato
Benjamín Sánchez-Lengeling
Dennis Sheberla
J. Aguilera-Iparraguirre
Timothy D. Hirzel
Ryan P. Adams
Alán Aspuru-Guzik
3DV
127
2,911
0
07 Oct 2016
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNN
SSL
485
28,901
0
09 Sep 2016
Molecular Graph Convolutions: Moving Beyond Fingerprints
Molecular Graph Convolutions: Moving Beyond Fingerprints
S. Kearnes
Kevin McCloskey
Marc Berndl
Vijay S. Pande
Patrick F. Riley
GNN
113
1,446
0
02 Mar 2016
Convolutional Networks on Graphs for Learning Molecular Fingerprints
Convolutional Networks on Graphs for Learning Molecular Fingerprints
David Duvenaud
D. Maclaurin
J. Aguilera-Iparraguirre
Rafael Gómez-Bombarelli
Timothy D. Hirzel
Alán Aspuru-Guzik
Ryan P. Adams
GNN
154
3,337
0
30 Sep 2015
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