A surrogate accelerated multicanonical Monte Carlo method for uncertainty quantification. - Keyi Wu; Jinglai Li (J. Comput. Phys., 2016)

Collective Influence Maximization. - Xudong Wu; Luoyi Fu; Keyi Wu; Bo Jiang 003; Xinbing Wang; Guihai Chen (MobiHoc, 2019)

Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions. - Peng Chen 024; Keyi Wu; Joshua Chen; Tom O'Leary-Roseberry; Omar Ghattas (NeurIPS, 2019)

A fast and scalable computational framework for large-scale and high-dimensional Bayesian optimal experimental design. - Keyi Wu; Peng Chen 024; Omar Ghattas (CoRR, 2020)

A fast and scalable computational framework for goal-oriented linear Bayesian optimal experimental design: Application to optimal sensor placement. - Keyi Wu; Peng Chen 024; Omar Ghattas (CoRR, 2021)

Derivative-informed projected neural network for large-scale Bayesian optimal experimental design. - Keyi Wu; Thomas O'Leary-Roseberry; Peng Chen 024; Omar Ghattas (CoRR, 2022)

Automated spacing measurement of formwork system members with 3D point cloud data. - Keyi Wu; Samuel A. Prieto; Eyob T. Mengiste; Borja Garcia de Soto (CoRR, 2023)

Bayesian model calibration for diblock copolymer thin film self-assembly using power spectrum of microscopy data. - Lianghao Cao; Keyi Wu; J. Tinsley Oden; Peng Chen 024; Omar Ghattas (CoRR, 2023)

An Offline-Online Decomposition Method for Efficient Linear Bayesian Goal-Oriented Optimal Experimental Design: Application to Optimal Sensor Placement. - Keyi Wu; Peng Chen 024; Omar Ghattas (SIAM J. Sci. Comput., 2023)

A Fast and Scalable Computational Framework for Large-Scale High-Dimensional Bayesian Optimal Experimental Design. - Keyi Wu; Peng Chen 024; Omar Ghattas (SIAM/ASA J. Uncertain. Quantification, 2023)

Large-Scale Bayesian Optimal Experimental Design with Derivative-Informed Projected Neural Network. - Keyi Wu; Thomas O'Leary-Roseberry; Peng Chen 024; Omar Ghattas (J. Sci. Comput., 2023)

Cocv: A compression algorithm for time-series data with continuous constant values in IoT-based monitoring systems. - Shengsheng Lin; Weiwei Lin 001; Keyi Wu; Songbo Wang; Minxian Xu; James Z. Wang 002 (Internet Things, 2024)