Wayne Isaac Tan Uy

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 11

Top Topics

Diffusion Process

Partially Observed

Probability Density

Differential Equations

Top Venues

Comput. Math. Appl.

SIAM J. Sci. Comput.

J. Sci. Comput.

Publications

Haoran Zhao, Wayne Isaac Tan Uy
GenFormer: A Deep-Learning-Based Approach for Generating Multivariate Stochastic Processes. CoRR (2024)
Wayne Isaac Tan Uy, Dirk Hartmann, Benjamin Peherstorfer
Operator inference with roll outs for learning reduced models from scarce and low-quality data. Comput. Math. Appl. 145 (2023)
Wayne Isaac Tan Uy, Yuepeng Wang, Yuxiao Wen, Benjamin Peherstorfer
Active Operator Inference for Learning Low-Dimensional Dynamical-System Models from Noisy Data. SIAM J. Sci. Comput. 45 (4) (2023)
Rodrigo Singh, Wayne Isaac Tan Uy, Benjamin Peherstorfer
Lookahead data-gathering strategies for online adaptive model reduction of transport-dominated problems. CoRR (2023)
Wayne Isaac Tan Uy, Dirk Hartmann, Benjamin Peherstorfer
Operator inference with roll outs for learning reduced models from scarce and low-quality data. CoRR (2022)
Wayne Isaac Tan Uy, Christopher R. Wentland, Cheng Huang, Benjamin Peherstorfer
Reduced models with nonlinear approximations of latent dynamics for model premixed flame problems. CoRR (2022)
Wayne Isaac Tan Uy, Benjamin Peherstorfer
Operator inference of non-Markovian terms for learning reduced models from partially observed state trajectories. CoRR (2021)
Wayne Isaac Tan Uy, Benjamin Peherstorfer
Operator Inference of Non-Markovian Terms for Learning Reduced Models from Partially Observed State Trajectories. J. Sci. Comput. 88 (3) (2021)
Wayne Isaac Tan Uy, Yuepeng Wang, Yuxiao Wen, Benjamin Peherstorfer
Active operator inference for learning low-dimensional dynamical-system models from noisy data. CoRR (2021)
Wayne Isaac Tan Uy, Mircea Grigoriu
Time evolution of the characteristic and probability density function of diffusion processes via neural networks. CoRR (2020)
Wayne Isaac Tan Uy, Benjamin Peherstorfer
Probabilistic error estimation for non-intrusive reduced models learned from data of systems governed by linear parabolic partial differential equations. CoRR (2020)