Следене
Carl J. Yang
Carl J. Yang
Assistant Professor of Computer Science at Emory University
Потвърден имейл адрес: emory.edu - Начална страница
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Позовавания
Позовавания
Година
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
3832017
Adversarial attack and defense on graph data: A survey
L Sun, Y Dou, C Yang, K Zhang, J Wang, SY Philip, L He, B Li
IEEE Transactions on Knowledge and Data Engineering 35 (8), 7693-7711, 2022
3772022
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
364*2020
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
2462021
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
1892021
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
1842021
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
1542022
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
1512022
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
1372021
Domain specialization as the key to make large language models disruptive: A comprehensive survey
C Ling, X Zhao, J Lu, C Deng, C Zheng, J Wang, T Chowdhury, Y Li, ...
arXiv preprint arXiv:2305.18703, 2023
1152023
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
1132019
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
1122018
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
992022
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
982022
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
972022
A survey on graph structure learning: Progress and opportunities
Y Zhu, W Xu, J Zhang, Y Du, J Zhang, Q Liu, C Yang, S Wu
arXiv preprint arXiv:2103.03036, 2021
932021
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
802020
Beyond efficiency: A systematic survey of resource-efficient large language models
G Bai, Z Chai, C Ling, S Wang, J Lu, N Zhang, T Shi, Z Yu, M Zhu, ...
arXiv preprint arXiv:2401.00625, 2024
792024
Graph auto-encoder via neighborhood wasserstein reconstruction
M Tang, C Yang, P Li
arXiv preprint arXiv:2202.09025, 2022
712022
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
682021
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