Enhancing Molecular Topological Information with Multi-Task Graph Neural Networks

被引：0

作者：

Jiang, Yelu ^{[1
,2
]}

Quan, Lijun ^{[1
,2
]}

Wu, Tingfang ^{[1
,2
]}

Lyu, Qiang ^{[1
,2
]}

机构：

[1] School of Computer Science and Technology, Soochow University, Jiangsu, Suzhou,215006, China

[2] Jiangsu Province Key Lab for Information Processing Technologies, Jiangsu, Suzhou,215006, China

来源：

Computer Engineering and Applications | 2023年 / 59卷 / 10期

关键词：

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Coarse-grained modeling - Deep learning - Forecasting - Large datasets - Learning systems - Molecular structure - Toxicity

引用

页码：86 / 93

共 50 条

[1] SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data
He, Chaoyang
Ceyani, Emir
Balasubramanian, Keshav
Annavaram, Murali
Avestimehr, Salman
[J]. THIRTY-SIXTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FOURTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE / THE TWELVETH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2022, : 6865 - 6873
[2] All in One: Multi-Task Prompting for Graph Neural Networks
Sun, Xiangguo
Cheng, Hong
Li, Jia
Liu, Bo
Guan, Jihong
[J]. PROCEEDINGS OF THE 29TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, KDD 2023, 2023, : 2120 - 2131
[3] Multi-Task Time Series Forecasting Based on Graph Neural Networks
Han, Xiao
Huang, Yongjie
Pan, Zhisong
Li, Wei
Hu, Yahao
Lin, Gengyou
[J]. ENTROPY, 2023, 25 (08)
[4] Machining feature and topological relationship recognition based on a multi-task graph neural network
Xia, Mingyuan
Zhao, Xianwen
Hu, Xiaofeng
[J]. ADVANCED ENGINEERING INFORMATICS, 2024, 62
[5] Multi-Task Mixture Density Graph Neural Networks for Predicting Catalyst Performance
Liang, Chen
Wang, Bowen
Hao, Shaogang
Chen, Guangyong
Heng, Pheng-Ann
Zou, Xiaolong
[J]. ADVANCED FUNCTIONAL MATERIALS, 2024,
[6] Convex Multi-Task Learning with Neural Networks
Ruiz, Carlos
Alaiz, Carlos M.
Dorronsoro, Jose R.
[J]. HYBRID ARTIFICIAL INTELLIGENT SYSTEMS, HAIS 2022, 2022, 13469 : 223 - 235
[7] Predicting In Vivo Compound Brain Penetration Using Multi-task Graph Neural Networks
Hamzic, Seid
Lewis, Richard
Desrayaud, Sandrine
Soylu, Cihan
Fortunato, Mike
Gerebtzoff, Gregori
Rodriguez-Perez, Raquel
[J]. JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2022, : 3180 - 3190
[8] Multi-Task Learning for Metaphor Detection with Graph Convolutional Neural Networks and Word Sense Disambiguation
Duong Minh Le
My Thai
Thien Huu Nguyen
[J]. THIRTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THE THIRTY-SECOND INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE AND THE TENTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2020, 34 : 8139 - 8146
[9] Multi-task graph neural networks for simultaneous prediction of global and atomic properties in ferromagnetic systems *
Pasini, Massimiliano Lupo
Zhang, Pei
Reeve, Samuel Temple
Choi, Jong Youl
[J]. MACHINE LEARNING-SCIENCE AND TECHNOLOGY, 2022, 3 (02):
[10] Multi-task neural networks for dealing with missing inputs
Garcia-Laencina, Pedro J.
Serrano, Jesus
Figueiras-Vidal, Anibal R.
Sancho-Gomez, Jose-Luis
[J]. BIO-INSPIRED MODELING OF COGNITIVE TASKS, PT 1, PROCEEDINGS, 2007, 4527 : 282 - +

← 1 2 3 4 5 →