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Brian J. Reich
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2020 – today
- 2023
- [j15]Hongjian Yang, Sofia Ruiz-Suarez, Brian J. Reich
, Yawen Guan, Ana G. Rappold
:
A Data-Fusion Approach to Assessing the Contribution of Wildland Fire Smoke to Fine Particulate Matter in California. Remote. Sens. 15(17): 4246 (2023) - [i8]Pratik Nag, Ying Sun, Brian J. Reich:
Spatio-temporal DeepKriging for Interpolation and Probabilistic Forecasting. CoRR abs/2306.11472 (2023) - [i7]Pratik Nag, Ying Sun, Brian J. Reich:
Bivariate DeepKriging for Large-scale Spatial Interpolation of Wind Fields. CoRR abs/2307.08038 (2023) - [i6]Nicholas Simafranca, Bryant Willoughby, Erin O'Neil, Sophie Farr, Brian J. Reich, Naomi Giertych, Margaret Johnson, Madeleine Pascolini-Campbell:
Modelling wildland fire burn severity in California using a spatial Super Learner approach. CoRR abs/2311.16187 (2023) - 2022
- [j14]Suman Majumder
, Yawen Guan, Brian J. Reich
, Arvind K. Saibaba
:
Kryging: geostatistical analysis of large-scale datasets using Krylov subspace methods. Stat. Comput. 32(5): 74 (2022) - [j13]Matthew J. Miller
, Matthew J. Cabral
, Elizabeth C. Dickey
, James M. LeBeau
, Brian J. Reich
:
Accounting for Location Measurement Error in Imaging Data With Application to Atomic Resolution Images of Crystalline Materials. Technometrics 64(1): 103-113 (2022) - 2021
- [j12]Rui Li
, Brian J. Reich
, Howard D. Bondell
:
Deep distribution regression. Comput. Stat. Data Anal. 159: 107203 (2021) - [j11]Arkaprava Roy
, Brian J. Reich
, Joseph Guinness, Russell T. Shinohara, Ana-Maria Staicu
:
Spatial Shrinkage Via the Product Independent Gaussian Process Prior. J. Comput. Graph. Stat. 30(4): 1068-1080 (2021) - [j10]Danielle Sass
, Bo Li, Brian J. Reich
:
Flexible and Fast Spatial Return Level Estimation Via a Spatially Fused Penalty. J. Comput. Graph. Stat. 30(4): 1124-1142 (2021) - [j9]Munir A. Winkel, Jonathan W. Stallrich
, Curtis B. Storlie
, Brian J. Reich
:
Sequential Optimization in Locally Important Dimensions. Technometrics 63(2): 236-248 (2021) - 2020
- [i5]Yuxiao Li
, Ying Sun, Brian J. Reich:
DeepKriging: Spatially Dependent Deep Neural Networks for Spatial Prediction. CoRR abs/2007.11972 (2020) - [i4]David B. Huberman, Brian J. Reich, Howard D. Bondell:
Nonparametric Conditional Density Estimation In A Deep Learning Framework For Short-Term Forecasting. CoRR abs/2008.07653 (2020)
2010 – 2019
- 2019
- [j8]An-Ting Jhuang, Montserrat Fuentes, Jacob L. Jones
, Giovanni Esteves, Chris M. Fancher
, Marschall Furman, Brian J. Reich
:
Spatial Signal Detection Using Continuous Shrinkage Priors. Technometrics 61(4): 494-506 (2019) - [c1]Haoyu Wang, Yawen Guan
, Brian J. Reich:
Nearest-Neighbor Neural Networks for Geostatistics. ICDM Workshops 2019: 196-205 - [i3]Rui Li, Howard D. Bondell, Brian J. Reich:
Deep Distribution Regression. CoRR abs/1903.06023 (2019) - [i2]Haoyu Wang, Yawen Guan, Brian J. Reich:
Nearest-Neighbor Neural Networks for Geostatistics. CoRR abs/1903.12125 (2019) - [i1]Neal S. Grantham, Brian J. Reich, Eric B. Laber, Krishna Pacifici, Robert R. Dunn, Noah Fierer, Matthew Gebert, Julia S. Allwood, Seth A. Faith:
Global forensic geolocation with deep neural networks. CoRR abs/1905.11765 (2019) - 2018
- [j7]Dominic A. Libera, A. Sankarasubramanian, Ashish Sharma
, Brian J. Reich
:
A non-parametric bootstrapping framework embedded in a toolkit for assessing water quality model performance. Environ. Model. Softw. 107: 25-33 (2018) - 2017
- [j6]Qiwei Li
, Michele Guindani
, Brian J. Reich
, Howard D. Bondell
, Marina Vannucci:
A Bayesian mixture model for clustering and selection of feature occurrence rates under mean constraints. Stat. Anal. Data Min. 10(6): 393-409 (2017) - 2015
- [j5]Yimin Kao, Brian J. Reich
, Curtis B. Storlie, Blake Anderson:
Malware Detection Using Nonparametric Bayesian Clustering and Classification Techniques. Technometrics 57(4): 535-546 (2015) - 2013
- [j4]Curtis B. Storlie, Brian J. Reich
, Jon C. Helton, Laura Painton Swiler, Cédric J. Sallaberry:
Analysis of computationally demanding models with continuous and categorical inputs. Reliab. Eng. Syst. Saf. 113: 30-41 (2013) - 2012
- [j3]Michael D. Porter
, Brian J. Reich
:
Evaluating temporally weighted kernel density methods for predicting the next event location in a series. Ann. GIS 18(3): 225-240 (2012)
2000 – 2009
- 2009
- [j2]Jungsoon Choi
, Montserrat Fuentes, Brian J. Reich
:
Spatial-temporal association between fine particulate matter and daily mortality. Comput. Stat. Data Anal. 53(8): 2989-3000 (2009) - [j1]Brian J. Reich
, Curtis B. Storlie, Howard D. Bondell
:
Variable Selection in Bayesian Smoothing Spline ANOVA Models: Application to Deterministic Computer Codes. Technometrics 51(2): 110-120 (2009)
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