| Bayesian optimization meets Bayesian optimal stopping Z Dai, H Yu, BKH Low, P Jaillet International Conference on Machine Learning, 1496-1506, 2019 | 55 | 2019 |
| Implicit posterior variational inference for deep Gaussian processes H Yu, Y Chen, Z Dai, KH Low, P Jaillet Advances in Neural Information Processing Systems 32: 33rd Annual Conference …, 2019 | 41 | 2019 |
| Stochastic variational inference for Bayesian sparse Gaussian process regression H Yu, T Nghia, BKH Low, P Jaillet 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 28 | 2019 |
| AdaTask: A Task-aware Adaptive Learning Rate Approach to Multi-task Learning E Yang, J Pan, X Wang, H Yu, L Shen, X Chen, L Xiao, J Jiang, G Guo 37th AAAI Conference on Artificial Intelligence (AAAI-23), 2022 | 18 | 2022 |
| On provably robust meta-Bayesian optimization Z Dai, Y Chen, H Yu, BKH Low, P Jaillet Uncertainty in Artificial Intelligence, 475-485, 2022 | 9 | 2022 |
| Convolutional Normalizing Flows for Deep Gaussian Processes H Yu, D Liu, BKH Low, P Jaillet International Joint Conference on Neural Networks (IJCNN'21), 2021 | 5 | 2021 |
| Recursive reasoning-based training-time adversarial machine learning Y Chen, Z Dai, H Yu, BKH Low, TH Ho Artificial Intelligence 315, 103837, 2023 | 3 | 2023 |
| Ad Recommendation in a Collapsed and Entangled World J Pan, W Xue, X Wang, H Yu, X Liu, S Quan, X Qiu, D Liu, L Xiao, J Jiang arXiv preprint arXiv:2403.00793, 2024 | 1 | 2024 |
| New Advances in Bayesian Inference for Gaussian Process and Deep Gaussian Process Models H YU National University of Singapore, 2020 | | 2020 |
Bryan Kian Hsiang LowAssociate Professor (with tenure), Department of Computer Science, National University of SingaporeVerified email at comp.nus.edu.sg
