3 papers
cs.LG2025
Big Batch Bayesian Active Learning by Considering Predictive Probabilities
Sebastian W. Ober, Samuel Power, Tom Diethe +1
We observe that BatchBALD, a popular acquisition function for batch Bayesian active learning for classification, can conflate epistemic and aleatoric uncertainty, leading to subopt…
cs.LG2024
Error bounds for particle gradient descent, and extensions of the log-Sobolev and Talagrand inequalities
Rocco Caprio, Juan Kuntz, Samuel Power +1
We prove non-asymptotic error bounds for particle gradient descent (PGD, Kuntz et al., 2023), a recently introduced algorithm for maximum likelihood estimation of large latent vari…
cs.LG2023
Momentum Particle Maximum Likelihood
Jen Ning Lim, Juan Kuntz, Samuel Power +1
Maximum likelihood estimation (MLE) of latent variable models is often recast as the minimization of a free energy functional over an extended space of parameters and probability d…