4 papers · 1 filter
Prior- and likelihood-free probabilistic inference with finite-sample calibration guarantees
Leonardo Cella, Emily C. Hector
Motivated by parametric models for which the likelihood is analytically unavailable, numerically unstable, or prohibitively expensive to compute or optimize, we develop a prior- an…
A new mixture model for spatiotemporal exceedances with flexible tail dependence
Ryan Li, Emily C. Hector, Brian J. Reich +1
We propose a new model and estimation framework for spatiotemporal streamflow exceedances above a threshold that flexibly captures asymptotic dependence and independence in the tai…
When the whole is greater than the sum of its parts: Scaling black-box inference to large data settings through divide-and-conquer
Emily C. Hector, Amanda Lenzi
Black-box methods such as deep neural networks are exceptionally fast at obtaining point estimates of model parameters due to their amortisation of the loss function computation, b…
Multivariate and Online Transfer Learning with Uncertainty Quantification
Jimmy Hickey, Jonathan P. Williams, Brian J. Reich +1
Untreated periodontitis causes inflammation within the supporting tissue of the teeth and can ultimately lead to tooth loss. Modeling periodontal outcomes is beneficial as they are…