Keyi Wu

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 12

Top Topics

High Dimensions

Experimental Design

Computational Framework

Monte Carlo Method

Top Venues

SIAM/ASA J. Uncertain. Quantification

J. Comput. Phys.

Publications

Shengsheng Lin, Weiwei Lin, Keyi Wu, Songbo Wang, Minxian Xu, James Z. Wang
Cocv: A compression algorithm for time-series data with continuous constant values in IoT-based monitoring systems. Internet Things 25 (2024)
Keyi Wu, Thomas O'Leary-Roseberry, Peng Chen, Omar Ghattas
Large-Scale Bayesian Optimal Experimental Design with Derivative-Informed Projected Neural Network. J. Sci. Comput. 95 (1) (2023)
Keyi Wu, Peng Chen, Omar Ghattas
A Fast and Scalable Computational Framework for Large-Scale High-Dimensional Bayesian Optimal Experimental Design. SIAM/ASA J. Uncertain. Quantification 11 (1) (2023)
Lianghao Cao, Keyi Wu, J. Tinsley Oden, Peng Chen, Omar Ghattas
Bayesian model calibration for diblock copolymer thin film self-assembly using power spectrum of microscopy data. CoRR (2023)
Keyi Wu, Peng Chen, Omar Ghattas
An Offline-Online Decomposition Method for Efficient Linear Bayesian Goal-Oriented Optimal Experimental Design: Application to Optimal Sensor Placement. SIAM J. Sci. Comput. 45 (1) (2023)
Keyi Wu, Samuel A. Prieto, Eyob T. Mengiste, Borja Garcia de Soto
Automated spacing measurement of formwork system members with 3D point cloud data. CoRR (2023)
Keyi Wu, Thomas O'Leary-Roseberry, Peng Chen, Omar Ghattas
Derivative-informed projected neural network for large-scale Bayesian optimal experimental design. CoRR (2022)
Keyi Wu, Peng Chen, Omar Ghattas
A fast and scalable computational framework for goal-oriented linear Bayesian optimal experimental design: Application to optimal sensor placement. CoRR (2021)
Keyi Wu, Peng Chen, Omar Ghattas
A fast and scalable computational framework for large-scale and high-dimensional Bayesian optimal experimental design. CoRR (2020)
Xudong Wu, Luoyi Fu, Keyi Wu, Bo Jiang, Xinbing Wang, Guihai Chen
Collective Influence Maximization. MobiHoc (2019)
Peng Chen, Keyi Wu, Joshua Chen, Tom O'Leary-Roseberry, Omar Ghattas
Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions. NeurIPS (2019)
Keyi Wu, Jinglai Li
A surrogate accelerated multicanonical Monte Carlo method for uncertainty quantification. J. Comput. Phys. 321 (2016)