| Federated Transfer Learning for EEG Signal Classification C Ju, D Gao, R Mane, B Tan, Y Liu, C Guan 2020 42nd Annual International Conference of the IEEE Engineering in …, 2020 | 210 | 2020 |
| Privacy-preserving heterogeneous federated transfer learning D Gao, Y Liu, A Huang, C Ju, H Yu, Q Yang 2019 IEEE International Conference on Big Data, 2552-2559, 2019 | 171 | 2019 |
| Deep polarized network for supervised learning of accurate binary hashing codes L Fan, KW Ng, C Ju, T Zhang, CS Chan IJCAI 20' Proceedings of the Twenty-Ninth International Joint Conference on …, 2020 | 155 | 2020 |
| HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography D Gao, C Ju, X Wei, Y Liu, T Chen, Q Yang NeurIPS'2019 Workshop on Federated Machine Learning for User Privacy and …, 2019 | 145 | 2019 |
| Tensor-cspnet: A novel geometric deep learning framework for motor imagery classification C Ju, C Guan IEEE Transactions on Neural Networks and Learning Systems 34, 10955-10969, 2022 | 104 | 2022 |
| Interaction-aware kalman neural networks for trajectory prediction C Ju, Z Wang, C Long, X Zhang, G Cong, DE Chang 2020 IEEE Intelligent Vehicles Symposium (IV), Las Vegas, NV, USA, 2020, pp …, 2020 | 95 | 2020 |
| Rethinking privacy preserving deep learning: How to evaluate and thwart privacy attacks L Fan, KW Ng, C Ju, T Zhang, C Liu, CS Chan, Q Yang Federated Learning: Privacy and Incentive, Springer, 32-50, 2020 | 81 | 2020 |
| Effective and efficient sports play retrieval with deep representation learning Z Wang, C Long, G Cong, C Ju Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 60 | 2019 |
| Privacy-preserving technology to help millions of people: Federated prediction model for stroke prevention C Ju, R Zhao, J Sun, X Wei, B Zhao, Y Liu, H Li, T Chen, X Zhang, D Gao, ... IJCAI'20 Workshop on Federated Learning for Data Privacy and Confidentiality …, 2020 | 51 | 2020 |
| Graph Neural Networks on SPD Manifolds for Motor Imagery Classification: A Perspective From the Time–Frequency Analysis C Ju, C Guan IEEE Transactions on Neural Networks and Learning Systems 35 (12), 17701-17715, 2023 | 41 | 2023 |
| Privacy Threats Against Federated Matrix Factorization D Gao, B Tan, C Ju, VW Zheng, Q Yang IJCAI'20 Workshop on Federated Learning for Data Privacy and Confidentiality …, 2020 | 29 | 2020 |
| Deep Optimal Transport for Domain Adaptation on SPD Manifolds C Ju, C Guan Artificial Intelligence 345, 104347, 2025 | 17* | 2025 |
| Deep Geodesic Canonical Correlation Analysis for Covariance-Based Neuroimaging Data C Ju, RJ Kobler, L Tang, C Guan, M Kawanabe The Twelfth International Conference on Learning Representations (ICLR 2024 …, 2024 | 8 | 2024 |
| Score-based Data Generation for EEG Spatial Covariance Matrices: Towards Boosting BCI Performance C Ju, RJ Kobler, C Guan 2023 45th Annual International Conference of the IEEE Engineering in …, 2023 | 7 | 2023 |
| Ternary hashing C Liu, L Fan, KW Ng, Y Jin, C Ju, T Zhang, CS Chan, Q Yang arXiv preprint arXiv:2103.09173, 2021 | 7 | 2021 |
| Representation learning for spatial graphs Z Wang, C Ju, G Cong, C Long arXiv preprint arXiv:1812.06668, 2018 | 5 | 2018 |
| Riemannian Flow Matching for Brain Connectivity Matrices via Pullback Geometry A Collas, C Ju, N Salvy, B Thirion The Thirty-ninth Annual Conference on Neural Information Processing Systems …, 2025 | 1 | 2025 |
| SPD Learning for Covariance-Based Neuroimaging Analysis: Perspectives, Methods, and Challenges C Ju, RJ Kobler, A Collas, M Kawanabe, C Guan, B Thirion arXiv preprint arXiv:2504.18882, 2025 | 1 | 2025 |
| Stochastic Inverse Reinforcement Learning C Ju NeurIPS 20' Workshop, 2019 | 1 | 2019 |
| Geometric Methods for Covariance-Based Neural Decoding C Ju Nanyang Technological University, 2024 | | 2024 |
Cuntai GuanPresident's Chair Professor, CCDS, Nanyang Technological UniversityVerified email at ntu.edu.sg
