8 citations · 8 across the 1 of their papers we have counts for
3 papers
stat.CO2026★ 8 cited
Scalable marginalization of correlated latent variables with applications to learning particle interaction kernels
Mengyang Gu, Xubo Liu, Xinyi Fang +1
Marginalization of latent variables or nuisance parameters is a fundamental aspect of Bayesian inference and uncertainty quantification. In this work, we focus on scalable marginal…
stat.CO2026
Fast data inversion for high-dimensional Ornstein-Uhlenbeck processes from noisy measurements
Yizi Lin, Xubo Liu, Paul Segall +1
In this work, we develop a scalable approach for a flexible latent factor model for high-dimensional dynamical systems. Each latent factor process has its own correlation and varia…
physics.comp-ph2024
Ab initio uncertainty quantification in scattering analysis of microscopy
Mengyang Gu, Yue He, Xubo Liu +1
Estimating parameters from data is a fundamental problem, customarily done by minimizing a loss function between a model and observed statistics. In scattering-based analysis, rese…