1 code implementation • 8 Nov 2023 • Shikai Fang, Xin Yu, Zheng Wang, Shibo Li, Mike Kirby, Shandian Zhe
To generalize Tucker decomposition to such scenarios, we propose Functional Bayesian Tucker Decomposition (FunBaT).
1 code implementation • 29 Sep 2023 • Shibo Li, Xin Yu, Wei Xing, Mike Kirby, Akil Narayan, Shandian Zhe
To overcome this problem, we propose Multi-Resolution Active learning of FNO (MRA-FNO), which can dynamically select the input functions and resolutions to lower the data cost as much as possible while optimizing the learning efficiency.
no code implementations • NeurIPS 2020 • Shibo Li, Wei Xing, Mike Kirby, Shandian Zhe
In many applications, the objective function can be evaluated at multiple fidelities to enable a trade-off between the cost and accuracy.
2 code implementations • 25 Mar 2020 • Shibo Li, Wei Xing, Mike Kirby, Shandian Zhe
Gaussian process regression networks (GPRN) are powerful Bayesian models for multi-output regression, but their inference is intractable.