| Provably Convergent Schr\" odinger Bridge with Applications to Probabilistic Time Series Imputation Y Chen*, W Deng*, S Fang*, F Li*, NT Yang, Y Zhang, K Rasul, S Zhe, ... The 40th International Conference on Machine Learning (ICML), 2023, 2023 | 31 | 2023 |
| Bayesian Streaming Sparse Tucker Decomposition S Fang, RM Kirby, S Zhe The 37th Conference on Uncertainty in Artificial Intelligence(UAI), 2021 | 24 | 2021 |
| Streaming Bayesian Deep Tensor Factorization S Fang, Z Wang, Z Pan, J Liu, S zhe The Thirty-eighth International Conference on Machine Learning (ICML), 2021, 2021 | 16 | 2021 |
| Probabilistic neural-kernel tensor decomposition C Tillinghast, S Fang, K Zhang, S Zhe 2020 IEEE International Conference on Data Mining (ICDM), 531-540, 2020 | 15 | 2020 |
| Analysis of multivariate scoring functions for automatic unbiased learning to rank T Yang, S Fang, S Li, Y Wang, Q Ai Proceedings of the 29th ACM International Conference on Information …, 2020 | 9 | 2020 |
| BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition S Fang, Q Wen, Y Luo, S Zhe, L Sun ICML 2024, 2024 | 8 | 2024 |
| Bayesian continuous-time tucker decomposition S Fang, A Narayan, R Kirby, S Zhe International Conference on Machine Learning, 6235-6245, 2022 | 7 | 2022 |
| Shandian Zhe. Probabilistic neural-kernel tensor decomposition C Tillinghast, S Fang, K Zhang 2020 IEEE International Conference on Data Mining (ICDM), 531-540, 0 | 6 | |
| Multi-omic integration of blood-based tumor-associated genomic and lipidomic profiles using machine learning models in metastatic prostate cancer S Fang, S Zhe, HM Lin, AA Azad, H Fettke, EM Kwan, L Horvath, B Mak, ... JCO Clinical Cancer Informatics 7, e2300057, 2023 | 5 | 2023 |
| Online bayesian sparse learning with spike and slab priors S Fang, S Zhe, K Lee, K Zhang, J Neville 2020 IEEE International Conference on Data Mining (ICDM), 142-151, 2020 | 5 | 2020 |
| Shandian Zhe. Streaming bayesian deep tensor factorization S Fang, Z Wang, Z Pan, J Liu International Conference on Machine Learning, 3133-3142, 0 | 5 | |
| Solving High Frequency and Multi-Scale PDEs with Gaussian Processes S Fang, M Cooley, D Long, S Li, R Kirby, S Zhe ICLR 2024, 2024 | 4 | 2024 |
| Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor S Fang, X Yu, Z Wang, S Li, RM Kirby, S Zhe ICLR 2024, 2024 | 3* | 2024 |
| Dynamic Tensor Decomposition via Neural Diffusion-Reaction Processes Z Wang*, S Fang*, S Li, S Zhe Advances in Neural Information Processing Systems 36, 2024 | 3 | 2024 |
| Streaming factor trajectory learning for temporal tensor decomposition S Fang, X Yu, S Li, Z Wang, M Kirby, S Zhe Advances in Neural Information Processing Systems 36, 56849-56870, 2023 | 3 | 2023 |
| MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model J Li, Y Liu, W Liu, S Fang, L Wang, C Xu, J Bian arXiv preprint arXiv:2409.07486, 2024 | 1 | 2024 |
| Diffusion-generative multi-fidelity learning for physical simulation Z Wang, S Li, S Fang, S Zhe arXiv preprint arXiv:2311.05606, 2023 | 1 | 2023 |
| Generalized Temporal Tensor Decomposition with Rank-revealing Latent-ODE P Chen, L Cheng, J Li, W Li, W Liu, J Bian, S Fang arXiv preprint arXiv:2502.06164, 2025 | | 2025 |
| Multi-omic prediction model for metastatic prostate cancer M Kohli, RM Kirby, S Fang, S Zhe US Patent App. 18/661,495, 2024 | | 2024 |
| Bayesian Tensor Learning for Dynamic High-Order Data S Fang The University of Utah, 2024 | | 2024 |
Shandian ZheSchool of Computing, University of UtahZweryfikowany adres z cs.utah.edu