3 papers
stat.ML2025
On the Effect of Regularization on Nonparametric Mean-Variance Regression
Eliot Wong-Toi, Alex Boyd, Vincent Fortuin +1
Uncertainty quantification is vital for decision-making and risk assessment in machine learning. Mean-variance regression models, which predict both a mean and residual noise for e…
stat.ML2025
Deep Continuous-Time State-Space Models for Marked Event Sequences
Yuxin Chang, Alex Boyd, Cao Xiao +4
Marked temporal point processes (MTPPs) model sequences of events occurring at irregular time intervals, with wide-ranging applications in fields such as healthcare, finance and so…
cs.LG2025
Bayesian Inference for Correlated Human Experts and Classifiers
Markelle Kelly, Alex Boyd, Sam Showalter +2
Applications of machine learning often involve making predictions based on both model outputs and the opinions of human experts. In this context, we investigate the problem of quer…