| Bayesian semi-supervised learning with graph gaussian processes YC Ng, N Colombo, R Silva Advances in Neural Information Processing Systems 31, 1683-1694, 2018 | 113 | 2018 |
| Gaussian processes on graphs via spectral kernel learning YC Zhi, YC Ng, X Dong IEEE Transactions on Signal and Information Processing over Networks, 2023 | 37 | 2023 |
| Scaling factorial hidden markov models: Stochastic variational inference without messages YC Ng, PM Chilinski, R Silva Advances in Neural Information Processing Systems 29, 4044-4052, 2016 | 18 | 2016 |
| A Dynamic Edge Exchangeable Model for Sparse Temporal Networks YC Ng, R Silva NIPS 2017 Workshop in Advances in Modeling and Learning Interactions from …, 2017 | 7 | 2017 |
| Transductive Kernels for Gaussian Processes on Graphs YC Zhi, FL Opolka, YC Ng, P Liò, X Dong arXiv preprint arXiv:2211.15322, 2022 | 1 | 2022 |
| Algorithms for Evolving Networks and Structured Predictions R Silva, YC Ng | | |
Ricardo SilvaProfessor of Statistical Machine Learning and Data Science, Department of Statistical Science, UCL在 stats.ucl.ac.uk 的电子邮件经过验证
