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 | 360 | 2017 |
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 | 307* | 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 | 304* | 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 | 162 | 2021 |
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 | 122 | 2021 |
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 | 122 | 2021 |
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 | 109 | 2018 |
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 | 105 | 2021 |
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 | 104 | 2019 |
GraphBLAST: A high-performance linear algebra-based graph framework on the GPU C Yang, A Buluç, JD Owens ACM Transactions on Mathematical Software (TOMS) 48 (1), 1-51, 2022 | 98 | 2022 |
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 | 84 | 2022 |
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 | 75 | 2022 |
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 | 72 | 2022 |
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 | 71 | 2022 |
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 | 71 | 2020 |
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 | 66 | 2018 |
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 | 63 | 2022 |
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 | 58 | 2021 |
Graph auto-encoder via neighborhood wasserstein reconstruction M Tang, C Yang, P Li arXiv preprint arXiv:2202.09025, 2022 | 56 | 2022 |
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 | 54 | 2020 |