3 papers
stat.AP2025
COWs and their Hybrids: A Statistical View of Custom Orthogonal Weights
Chad Schafer, Larry Wasserman, Mikael Kuusela
A recurring challenge in high energy physics is inference of the signal component from a distribution for which observations are assumed to be a mixture of signal and background ev…
stat.CO2023
Posterior Uncertainty Estimation via a Monte Carlo Procedure Specialized for Data Assimilation
Michael Stanley, Mikael Kuusela, Brendan Byrne +1
Through the Bayesian lens of data assimilation, uncertainty on model parameters is traditionally quantified through the posterior covariance matrix. However, in modern settings inv…
stat.AP2023
Statistical constraints on climate model parameters using a scalable cloud-based inference framework
James Carzon, Bruno R. de Abreu, Leighton Regayre +5
Atmospheric aerosols influence the Earth's climate, primarily by affecting cloud formation and scattering visible radiation. However, aerosol-related physical processes in climate…