4 citations · 4 across the 5 of their papers we have counts for
3 papers · 1 filter
Amortized Bayesian Local Interpolation NetworK: Fast covariance parameter estimation for Gaussian Processes
Brandon R. Feng, Reetam Majumder, Brian J. Reich +1
Gaussian processes (GPs) are a ubiquitous tool for geostatistical modeling with high levels of flexibility and interpretability, and the ability to make predictions at unseen spati…
Stochastic Gradient MCMC for Massive Geostatistical Data
Mohamed A. Abba, Brian J. Reich, Reetam Majumder +1
Gaussian processes (GPs) are commonly used for prediction and inference for spatial data analyses. However, since estimation and prediction tasks have cubic time and quadratic memo…
A Bayesian shrinkage estimator for transfer learning
Mohamed A. Abba, Jonathan P. Williams, Brian J. Reich
Transfer learning (TL) has emerged as a powerful tool to supplement data collected for a target task with data collected for a related source task. The Bayesian framework is natura…