2 papers
cs.LG2025
An Entropic Metric for Measuring Calibration of Machine Learning Models
Daniel James Sumler, Lee Devlin, Simon Maskell +1
Understanding the confidence with which a machine learning model classifies an input datum is an important, and perhaps under-investigated, concept. In this paper, we propose a new…
stat.AP2023
An SMC Algorithm on Distributed Memory with an Approx. Optimal L-Kernel
Conor Rosato, Alessandro Varsi, Joshua Murphy +1
Calibrating statistical models using Bayesian inference often requires both accurate and timely estimates of parameters of interest. Particle Markov Chain Monte Carlo (p-MCMC) and…