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Carl J. Yang
Carl J. Yang
Assistant Professor of Computer Science at Emory University
Verified email at emory.edu - Homepage
Title
Cited by
Cited by
Year
Bridging collaborative filtering and semi-supervised learning: a neural approach for poi recommendation
C Yang, L Bai, C Zhang, Q Yuan, J Han
Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017
3522017
Heterogeneous network representation learning: A unified framework with survey and benchmark
C Yang, Y Xiao, Y Zhang, Y Sun, J Han
IEEE Transactions on Knowledge and Data Engineering 34 (10), 4854-4873, 2020
281*2020
Adversarial attack and defense on graph data: A survey
L Sun, Y Dou, C Yang, J Wang, PS Yu, B Li
arXiv preprint arXiv:1812.10528, 2018
265*2018
Fedgraphnn: A federated learning system and benchmark for graph neural networks
C He, K Balasubramanian, E Ceyani, C Yang, H Xie, L Sun, L He, L Yang, ...
arXiv preprint arXiv:2104.07145, 2021
1392021
Federated graph classification over non-iid graphs
H Xie, J Ma, L Xiong, C Yang
Advances in neural information processing systems 34, 18839-18852, 2021
992021
I know you'll be back: Interpretable new user clustering and churn prediction on a mobile social application
C Yang, X Shi, L Jie, J Han
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018
992018
Subgraph federated learning with missing neighbor generation
K Zhang, C Yang, X Li, L Sun, SM Yiu
Advances in Neural Information Processing Systems 34, 6671-6682, 2021
982021
Conditional structure generation through graph variational generative adversarial nets
C Yang, P Zhuang, W Shi, A Luu, P Li
Advances in neural information processing systems 32, 2019
962019
Transfer learning of graph neural networks with ego-graph information maximization
Q Zhu, C Yang, Y Xu, H Wang, C Zhang, J Han
Advances in Neural Information Processing Systems 34, 1766-1779, 2021
852021
When do gnns work: Understanding and improving neighborhood aggregation
Y Xie, S Li, C Yang, RCW Wong, J Han
IJCAI'20: Proceedings of the Twenty-Ninth International Joint Conference on …, 2020
662020
mvn2vec: Preservation and collaboration in multi-view network embedding
Y Shi, F Han, X He, X He, C Yang, J Luo, J Han
arXiv preprint arXiv:1801.06597, 2018
652018
Brain network transformer
X Kan, W Dai, H Cui, Z Zhang, Y Guo, C Yang
Advances in Neural Information Processing Systems 35, 25586-25599, 2022
592022
Fbnetgen: Task-aware gnn-based fmri analysis via functional brain network generation
X Kan, H Cui, J Lukemire, Y Guo, C Yang
International Conference on Medical Imaging with Deep Learning, 618-637, 2022
582022
Braingb: a benchmark for brain network analysis with graph neural networks
H Cui, W Dai, Y Zhu, X Kan, AAC Gu, J Lukemire, L Zhan, L He, Y Guo, ...
IEEE transactions on medical imaging 42 (2), 493-506, 2022
582022
On positional and structural node features for graph neural networks on non-attributed graphs
H Cui, Z Lu, P Li, C Yang
Proceedings of the 31st ACM International Conference on Information …, 2022
572022
Interpretable graph neural networks for connectome-based brain disorder analysis
H Cui, W Dai, Y Zhu, X Li, L He, C Yang
International Conference on Medical Image Computing and Computer-Assisted …, 2022
502022
Understanding structural vulnerability in graph convolutional networks
L Chen, J Li, Q Peng, Y Liu, Z Zheng, C Yang
arXiv preprint arXiv:2108.06280, 2021
502021
Local coordinate concept factorization for image representation
H Liu, Z Yang, C Yang, Z Wu, X Li
IEEE Transactions on Neural Networks and Learning Systems 25 (6), 1071-1082, 2013
502013
MultiSage: Empowering GCN with contextualized multi-embeddings on web-scale multipartite networks
C Yang, A Pal, A Zhai, N Pancha, J Han, C Rosenberg, J Leskovec
Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020
482020
Node, motif and subgraph: Leveraging network functional blocks through structural convolution
C Yang, M Liu, VW Zheng, J Han
2018 IEEE/ACM International Conference on Advances in Social Networks …, 2018
482018
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Articles 1–20