Crossref Citations
This Book has been
cited by the following publications. This list is generated based on data provided by Crossref.
Yadati, Naganand
Gao, Tingran
Asoodeh, Shahab
Talukdar, Partha
and
Louis, Anand
2021.
Advances in Knowledge Discovery and Data Mining.
Vol. 12712,
Issue. ,
p.
447.
Fazaeli, Mohsen
and
Momtazi, Saeedeh
2022.
Node classifications with DjCaNE: Disjoint content and network embedding.
Journal of Information Science,
p.
016555152211110.
Casas-Roma, Jordi
Martinez-Heras, Eloy
Solé-Ribalta, Albert
Solana, Elisabeth
Lopez-Soley, Elisabet
Vivó, Francesc
Diaz-Hurtado, Marcos
Alba-Arbalat, Salut
Sepulveda, Maria
Blanco, Yolanda
Saiz, Albert
Borge-Holthoefer, Javier
Llufriu, Sara
and
Prados, Ferran
2022.
Applying multilayer analysis to morphological, structural, and functional brain networks to identify relevant dysfunction patterns.
Network Neuroscience,
Vol. 6,
Issue. 3,
p.
916.
Duan, Yijun
Liu, Xin
Jatowt, Adam
Yu, Hai-tao
Lynden, Steven
Kim, Kyoung-Sook
and
Matono, Akiyoshi
2022.
Dual Cost-sensitive Graph Convolutional Network.
p.
1.
Zhuo, Weipeng
Zhao, Ziqi
Ho Chiu, Ka
Li, Shiju
Ha, Sangtae
Lee, Chul-Ho
and
Gary Chan, S.-H.
2022.
GRAFICS: Graph Embedding-based Floor Identification Using Crowdsourced RF Signals.
p.
1051.
Zhang, Shicheng
Zhang, Laixian
Qin, Mingyu
Guo, Huichao
and
Wei, Wei
2022.
TensorRT acceleration based on deep learning photoelectric target detection.
p.
21.
Yuan, Hao
Yu, Haiyang
Gui, Shurui
and
Ji, Shuiwang
2022.
Explainability in Graph Neural Networks: A Taxonomic Survey.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
p.
1.
Huang, Xin
Kim, Jongryool
Rees, Bradley
and
Lee, Chul-Ho
2022.
Characterizing the Efficiency of Graph Neural Network Frameworks with a Magnifying Glass.
p.
160.
Lachaud, Guillaume
Conde-Cespedes, Patricia
and
Trocan, Maria
2022.
Mathematical Expressiveness of Graph Neural Networks.
Mathematics,
Vol. 10,
Issue. 24,
p.
4770.
Jia, Mingshan
Gabrys, Bogdan
and
Musial, Katarzyna
2023.
A Network Science Perspective of Graph Convolutional Networks: A Survey.
IEEE Access,
Vol. 11,
Issue. ,
p.
39083.
Arabyarmohammadi, Sara
Corredor, German
Zhou, Yufei
López de Rodas, Miguel
Schalper, Kurt
and
Madabhushi, Anant
2023.
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023.
Vol. 14225,
Issue. ,
p.
797.
Li, Xiaoyu
Wang, Jingnan
Huang, Binhua
Liu, Chengliang
Liu, Yiwen
Zhang, Yupo
Yi, Zhengkun
and
Wu, Xinyu
2023.
TGCN-P: A TCN-GCN Network With Weighted Graph Constructed by Pearson Correlation Coefficient for Human Motion Tracking.
p.
310.
Duan, Yijun
Liu, Xin
Jatowt, Adam
Yu, Hai-tao
Lynden, Steven
Kim, Kyoung-Sook
and
Matono, Akiyoshi
2023.
Machine Learning and Knowledge Discovery in Databases.
Vol. 13714,
Issue. ,
p.
20.
Wang, Yiqi
Li, Chaozhuo
Liu, Zheng
Li, Mingzheng
Tang, Jiliang
Xie, Xing
Chen, Lei
and
Yu, Philip S.
2023.
An Adaptive Graph Pre-training Framework for Localized Collaborative Filtering.
ACM Transactions on Information Systems,
Vol. 41,
Issue. 2,
p.
1.
Gu, Yujie
Sun, Huiyan
Wang, Yansong
and
Shi, Haobo
2023.
Improve Robustness of Graph Neural Networks: Multi-hop Neighbors Meet Homophily-based Truncation Defense.
p.
1.
Xie, Yaochen
Xu, Zhao
Zhang, Jingtun
Wang, Zhengyang
and
Ji, Shuiwang
2023.
Self-Supervised Learning of Graph Neural Networks: A Unified Review.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
Vol. 45,
Issue. 2,
p.
2412.
Werner, Luisa
Layaïda, Nabil
Genevès, Pierre
and
Chlyah, Sarah
2023.
Knowledge Enhanced Graph Neural Networks.
p.
1.
Das, Sanjiv
Huang, Xin
Adeshina, Soji
Yang, Patrick
and
Bachega, Leonardo
2023.
Credit Risk Modeling with Graph Machine Learning.
INFORMS Journal on Data Science,
Vol. 2,
Issue. 2,
p.
197.
Lee, Yeonjung
Ozer, Mert
Corman, Steven R.
and
Davulcu, Hasan
2023.
Identifying Behavioral Factors Leading to Differential Polarization Effects of Adversarial Botnets.
ACM SIGAPP Applied Computing Review,
Vol. 23,
Issue. 2,
p.
44.
Qin, Xiao
Sheikh, Nasrullah
Lei, Chuan
Reinwald, Berthold
and
Domeniconi, Giacomo
2023.
SEIGN: A Simple and Efficient Graph Neural Network for Large Dynamic Graphs.
p.
2850.