3 papers
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…
stat.AP2026
Model-free estimation in scattering analysis of microscopy
Tong Lin, Jinseok Lee, Matt Helgeson +3
The mean squared displacement (MSD) of particles or probes is commonly estimated from microscopy videos using particle tracking approaches, which rely on tuning parameters manually…
stat.AP2026
Unsupervised cell segmentation by fast Gaussian Processes
Laura Baracaldo, Blythe King, Haoran Yan +3
Cell boundary information is crucial for analyzing cell behaviors from time-lapse microscopy videos. Existing supervised cell segmentation tools, such as ImageJ, require tuning var…