GNNBook@2023

Lingfei Wu, Yu Chen, Heng Ji, Yunyao Li. Deep Learning on Graphs for Natural Language Processing. NAACL 2021
Lingfei Wu, Yu Chen, Heng Ji, Bang Liu. Deep Learning on Graphs for Natural Language Processing. SIGIR 2021
Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang, Yukuo Cen, Jiezhong Qiu, Jie Tang, Chuan Shi, Yanfang Ye, Jiawei Zhang, Philip S. Yu. Graph Representation Learning:Foundations, Methods, Applications and Systems. KDD 2021
Lingfei Wu, Yu Chen, Heng Ji, Yunyao Li, Bang Liu. Deep Learning on Graphs for Natural Language Processing. KDD 2021
Jian Tang, Fei Wang, Feixiong Cheng. Artificial Intelligence for Drug Discovery. KDD 2021
Chuxu Zhang, Jundong Li, Meng Jiang. Data Efficient Learning on Graphs. KDD 2021
Lingfei Wu, Yu Chen, Heng Ji, Yunyao Li, Bang Liu. Deep Learning on Graphs for Natural Language Processing. IJCAI 2021
Yao Ma, Wei Jin, Jiliang Tang, Yiqi Wang, Tyler Derr. Graph Neural Networks: Models and Applications. AAAI 2021
Jian Tang, Fei Wang, Feixiong Cheng. Artificial Intelligence for Drug Discovery. AAAI 2021
Yao Ma, Wei Jin, Jiliang Tang, Lingfei Wu and Tengfei Ma. Graph Neural Networks: Models and Applications. SIGIR 2021
Yu Rong, Wenbing Huang, Tingyang Xu, Hong Cheng, Junzhou Huang, Yao Ma, Yiqi Wang, Tyler Derr, Lingfei Wu and Tengfei Ma. Deep Graph Learning: Foundations, Advances and Applications. KDD 2020
Xavier Bresson, Yann LeCun, Stanley Osher, Rene Vidal, Rebecca Willett. Deep Geometric Learning of Big Data and Applications. IPAM 2019
Marinka Zitnik, Jure Leskovec. Deep Learning for Network Biology. ISMB 2018
William L. Hamilton, Rex Ying, Jure Leskovec, Rok Sosic. Representation Learning on Networks. WWW 2018

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