Spatial-temporal association between fine particulate matter and daily mortality. - Jungsoon Choi; Montserrat Fuentes; Brian J. Reich (Comput. Stat. Data Anal., 2009)

Variable Selection in Bayesian Smoothing Spline ANOVA Models: Application to Deterministic Computer Codes. - Brian J. Reich; Curtis B. Storlie; Howard D. Bondell (Technometrics, 2009)

Evaluating temporally weighted kernel density methods for predicting the next event location in a series. - Michael D. Porter; Brian J. Reich (Ann. GIS, 2012)

Analysis of computationally demanding models with continuous and categorical inputs. - Curtis B. Storlie; Brian J. Reich; Jon C. Helton; Laura Painton Swiler; Cédric J. Sallaberry (Reliab. Eng. Syst. Saf., 2013)

Malware Detection Using Nonparametric Bayesian Clustering and Classification Techniques. - Yimin Kao; Brian J. Reich; Curtis B. Storlie; Blake Anderson (Technometrics, 2015)

A Bayesian mixture model for clustering and selection of feature occurrence rates under mean constraints. - Qiwei Li 001; Michele Guindani; Brian J. Reich; Howard D. Bondell; Marina Vannucci (Stat. Anal. Data Min., 2017)

A non-parametric bootstrapping framework embedded in a toolkit for assessing water quality model performance. - Dominic A. Libera; A. Sankarasubramanian; Ashish Sharma 002; Brian J. Reich (Environ. Model. Softw., 2018)

Nearest-Neighbor Neural Networks for Geostatistics. - Haoyu Wang; Yawen Guan; Brian J. Reich (ICDM Workshops, 2019)

Global forensic geolocation with deep neural networks. - Neal S. Grantham; Brian J. Reich; Eric B. Laber; Krishna Pacifici; Robert R. Dunn; Noah Fierer; Matthew Gebert; Julia S. Allwood; Seth A. Faith (CoRR, 2019)

Spatial Signal Detection Using Continuous Shrinkage Priors. - An-Ting Jhuang; Montserrat Fuentes; Jacob L. Jones; Giovanni Esteves; Chris M. Fancher; Marschall Furman; Brian J. Reich (Technometrics, 2019)

DeepKriging: Spatially Dependent Deep Neural Networks for Spatial Prediction. - Yuxiao Li 003; Ying Sun 002; Brian J. Reich (CoRR, 2020)

Nonparametric Conditional Density Estimation In A Deep Learning Framework For Short-Term Forecasting. - David B. Huberman; Brian J. Reich; Howard D. Bondell (CoRR, 2020)

Deep distribution regression. - Rui Li 061; Brian J. Reich; Howard D. Bondell (Comput. Stat. Data Anal., 2021)

Spatial Shrinkage Via the Product Independent Gaussian Process Prior. - Arkaprava Roy; Brian J. Reich; Joseph Guinness; Russell T. Shinohara; Ana-Maria Staicu (J. Comput. Graph. Stat., 2021)

Flexible and Fast Spatial Return Level Estimation Via a Spatially Fused Penalty. - Danielle Sass; Bo Li; Brian J. Reich (J. Comput. Graph. Stat., 2021)

Sequential Optimization in Locally Important Dimensions. - Munir A. Winkel; Jonathan W. Stallrich; Curtis B. Storlie; Brian J. Reich (Technometrics, 2021)

Kryging: geostatistical analysis of large-scale datasets using Krylov subspace methods. - Suman Majumder; Yawen Guan; Brian J. Reich; Arvind K. Saibaba (Stat. Comput., 2022)

Accounting for Location Measurement Error in Imaging Data With Application to Atomic Resolution Images of Crystalline Materials. - Matthew J. Miller; Matthew J. Cabral; Elizabeth C. Dickey; James M. LeBeau; Brian J. Reich (Technometrics, 2022)

Spatio-temporal DeepKriging for Interpolation and Probabilistic Forecasting. - Pratik Nag; Ying Sun 002; Brian J. Reich (CoRR, 2023)

Modelling wildland fire burn severity in California using a spatial Super Learner approach. - Nicholas Simafranca; Bryant Willoughby; Erin O'Neil; Sophie Farr; Brian J. Reich; Naomi Giertych; Margaret Johnson; Madeleine Pascolini-Campbell (CoRR, 2023)

A Data-Fusion Approach to Assessing the Contribution of Wildland Fire Smoke to Fine Particulate Matter in California. - Hongjian Yang; Sofia Ruiz-Suarez; Brian J. Reich; Yawen Guan; Ana G. Rappold (Remote. Sens., 2023)

Amortized Bayesian Local Interpolation NetworK: Fast covariance parameter estimation for Gaussian Processes. - Brandon R. Feng; Reetam Majumder; Brian J. Reich; Mohamed A. Abba (CoRR, 2024)

A spatiotemporal optimization engine for prescribed burning in the Southeast US. - Reetam Majumder; Adam J. Terando; John Kevin Hiers; Jaime A. Collazo; Brian J. Reich (Ecol. Informatics, 2025)

STACI: Spatio-Temporal Aleatoric Conformal Inference. - Brandon R. Feng; David Keetae Park; Xihaier Luo; Arantxa Urdangarin; Shinjae Yoo; Brian J. Reich (CoRR, 2025)

Bivariate DeepKriging for Large-Scale Spatial Interpolation of Wind Fields. - Pratik Nag; Ying Sun 002; Brian J. Reich (Technometrics, 2025)