4 citations · 4 across the 5 of their papers we have counts for
7 papers
DANCE: Doubly Adaptive Neighborhood Conformal Estimation
Brandon R. Feng, Brian J. Reich, Daniel Beaglehole +7
The recent developments of complex deep learning models have led to unprecedented ability to accurately predict across multiple data representation types. Conformal prediction for…
Causal Spatial Quantile Regression
Yan Gong, Reetam Majumder, Brian J. Reich +1
Treatment effects in a wide range of economic, environmental, and epidemiological applications often vary across space, and understanding the heterogeneity of causal effects across…
STACI: Spatio-Temporal Aleatoric Conformal Inference
Brandon R. Feng, David Keetae Park, Xihaier Luo +3
Fitting Gaussian Processes (GPs) provides interpretable aleatoric uncertainty quantification for estimation of spatio-temporal fields. Spatio-temporal deep learning models, while s…
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…
Semiparametric Estimation of the Shape of the Limiting Bivariate Point Cloud
Reetam Majumder, Benjamin A. Shaby, Brian J. Reich +1
We propose a model to flexibly estimate joint tail properties by exploiting the convergence of an appropriately scaled point cloud onto a compact limit set. Characteristics of the…