Keyword Search
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CC = Baltimore Convention Center, H = Hilton Baltimore
* = applied session ! = JSM meeting theme
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Keyword Search Criteria: Gaussian process returned 56 record(s)
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Sunday, 07/30/2017
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Bayesian Multispecies Ecological Models for Paleoclimate Reconstruction Using Inverse Prediction
John Tipton, Colorado State University; Mevin Hooten, Colorado State University
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Barycentric Gaussian Processes for Nonparametric Regression
Cheng Li, National University of Singapore; Sanvesh Srivastava, The University of Iowa; David B. Dunson, Duke University
2:25 PM
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Estimating Parameters in Complex Systems with Functional Outputs - a Wavelet-Based Approximate Bayesian Computation Approach
Ruijin Lu, Virginia Polytechnic Institute and State University; Hongxiao Zhu, Assistant Professor, Virginia Tech; Chen Ming, Department of Mechanical Engineering, Virginia Tech; Anupam K. Gupta, Department of Mechanical Engineering, Virginia Tech; Rolf Muller, Department of Mechanical Engineering, Virginia Tech
2:35 PM
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Functional Autoregression for Sparsely Sampled Data
Daniel Kowal, Cornell University; David S Matteson, Cornell University; David Ruppert, Cornell University
2:50 PM
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Practical Heteroskedastic Gaussian Process Modeling for Large Simulation Experiments
Mickael Binois; Robert Gramacy, Virginia Tech Department of Statistics; Mike Ludkovski, University of California, Santa Barbara
4:05 PM
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Robust Parameter Design Using Computer Experiments
V. Roshan Joseph, Georgia Institute of Technology; Li Gu, Wells Fargo & Company; Shan Ba, Procter & Gamble Company; William Myers, The Procter & Gamble Company
4:45 PM
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Nonparametric Functional Calibration of Computer Models
Andrew Brown, Clemson University; Sez Atamturktur, Glenn Department of Civil Engineering, Clemson University
5:05 PM
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Bayesian Regression Using an Approximated Solution to the Penalized Least Squares Minimization Problem
Eduardo Trujillo Rivera
5:25 PM
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Bayesian Emulators for Composition Distribution of Kepler's Sub-Neptune Planets
Anirban Mondal, Case Western Reserve University; Angie Wolfgang, The Pennsylvania State University
5:35 PM
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Monday, 07/31/2017
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Bayesian Methods for Image Texture Analysis with Applications to Cancer Radiomics
Xiao Li, University of Texas, School of Public Health, Department of Biostatistics; Michele Guindani, University of California, Irvine; Chaan Ng, The University of Texas MD Anderson C; Brian P. Hobbs, The University of Texas MD Anderson Cancer Center
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Computer Model Calibration via the Ensemble Kalman Filter
Seiyon Lee, Pennsylvania State University; Murali Haran, Pennsylvania State University; Klaus Keller, Pennsylvania State University
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Controlling Sources of Inaccuracy in Stochastic Kriging
Wenjia Wang, Georgia Institute of Technology
8:35 AM
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Computer Model Calibration via the Ensemble Kalman Filter
Seiyon Lee, Pennsylvania State University; Murali Haran, Pennsylvania State University; Klaus Keller, Pennsylvania State University
8:50 AM
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Learning Non-Parametric Binary Regression Using Flixible Power Link Function with GP Priors
Abhishek Bishoyi, University of Connecticut; Xiaojing Wang, University of Connecticut; Dipak K Dey, university of connecticut
9:35 AM
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Bayesian Multiscale Spatial Models for Big Data
Raj Guahniyogi, UCSC
9:35 AM
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Nonseparable Gaussian Stochastic Process: a Unified View and Computational Strategy
Mengyang Gu, Johns Hopkins University; Yanxun Xu, Johns Hopkins University; Barbara Engelhardt, Princeton University
10:35 AM
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Large-P Small-N Nonparametric Regression and Additive-Interactive Response Functions
Surya T Tokdar, Duke University
11:00 AM
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Gaussian Processes for Individualized Continuous Treatment Rule Estimation
Pavel Shvechikov, Higher School of Economics; Evgeniy Riabenko, Higher School of Economics
11:05 AM
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Statistical Compression and Conditional Emulation
Joseph Guinness, NC State University; Dorit Hammerling, National Center for Atmospheric Research
11:15 AM
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Bayesian Methods for Image Texture Analysis with Applications to Cancer Radiomics
Xiao Li, University of Texas, School of Public Health, Department of Biostatistics; Michele Guindani, University of California, Irvine; Chaan Ng, The University of Texas MD Anderson C; Brian P. Hobbs, The University of Texas MD Anderson Cancer Center
11:20 AM
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Bayesian Gaussian Process Models on Spaces of Sufficient Dimension Reduction
Peter Marcy, Los Alamos National Laboratory
11:35 AM
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Gaussian Process Ensembles
Gregory Watson; Donatello Telesca, UCLA
11:50 AM
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Bayesian Semiparametric Covariance Function Estimation for Stationary Gaussian Processes by Overwhelming Force
John Ensley
2:35 PM
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A Flexible Joint Longitudinal-Survival Model for a Simultaneous Modeling of Multiple Longitudinal Biomarkers
Sepehr Akhavan Masouleh, UC Irvine; Babak Shahbaba, University of California, Irvine; Alexander Vandenberg-Rodes, UC Irvine; Daniel L. Gillen, University of California, Irvine
3:25 PM
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Tuesday, 08/01/2017
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Combining Functional Data with Hierarchical Gaussian Process Models
Valerie Poynor, California State University, Fullerton; Stephan Munch, Southwest Fisheries Science Center
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A New Nonparametric Estimation Method for multi-fractional Gaussian proces and Its Minimax Properties
Jinqi Shen, University of Michigan; Tailen Hsing, University of Michigan
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Sequential Computer Experiments for Failure Probability Estimation --- a Floor System Example
Hao Chen, University of British Columbia; William James Welch, University of British Columbia
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A Gaussian Process Approach for Estimating Treatment Assignment Mechanisms
Brian Vegetabile, University of California, Irvine; Hal Stern, University of California, Irvine
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Bayesian Semiparametric Modeling of Near Infra-Red Spectroscopy Data
Timothy D Johnson, University of Michigan
8:35 AM
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Process Convolution Approaches for Modeling Interacting Trajectories
Henry Scharf, Colorado State University; Mevin Hooten, Colorado State University; Devin Johnson, NOAA Alaska Fisheries Science Center; John Durban, NOAA Southwest Fisheries Science Center
8:35 AM
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A Mixture of Gaussian and Student's T Errors for a Robust and Accurate Parameter Estimation
Hyungsuk Tak, SAMSI; Justin A. Ellis, Jet Propulsion Laboratory; Sujit K Ghosh, North Carolina State University
8:50 AM
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Sparse Dynamic Spatio-Temporal Modeling Using Implied Advection
Robert Richardson, Brinham Young University
8:55 AM
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Bayesian Inference in the Presence of Intractable Normalizing Functions
Jaewoo Park, Penn State University
9:20 AM
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Multi-Resolution Approximations of Gaussian Processes for Big Spatial Data
Wenlong Gong, Texas A&M University
9:20 AM
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Sequential Computer Experiments for Failure Probability Estimation --- a Floor System Example
Hao Chen, University of British Columbia; William James Welch, University of British Columbia
9:20 AM
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A Gaussian Process Approach for Estimating Treatment Assignment Mechanisms
Brian Vegetabile, University of California, Irvine; Hal Stern, University of California, Irvine
9:55 AM
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Local Variable Selection in Sequential Optimization
Munir Winkel, North Carolina State University; Brian Reich, NCSU; Jonathan W. Stallings, North Carolina State University
2:05 PM
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Testing for Model Adequacy in Censored Location-Scale Families
Sundarraman Subramanian, New Jersey Institute of Technology
2:20 PM
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A Sequential Split-Conquer-Combine Approach for Gaussian Process Modeling in Computer Experiments
Ying Hung; Minge Xie, Rutgers University; Chengrui Li, Rutgers University
3:20 PM
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Wednesday, 08/02/2017
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Mixed Eff ects Material Strength Models with Model Discrepancy
Jason Bernstein; Kathleeen Schmidt, Lawrence Livermore National Laboratory; Ana Kupresanin, Lawrence Livermore National Laboratory; Jeff Florando, Lawrence Livermore National Laboratory; Nathan Barton, Lawrence Livermore National Laboratory
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A Class of Nonseparable and Nonstationary Covariance Functions for Multi-Ouput Gaussian Process
Pulong Ma, Department of Mathematical Sciences, University of Cincinnati; Bledar Alex Konomi, Department of Mathematical Sciences, University of Cincinnati; Emily L. Kang, University of Cincinnati
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Association Study of Children's Methylation and Growth Trajectory Using Functional Mixed Models
Colleen McKendry, North Carolina State University; Arnab Maity, North Carolina State University; Jung-Ying Tzeng, North Carolina State University
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Designing Computer Experiments to Maximize Prediction Accuracy
Erin Leatherman, West Virginia University; Angela Dean, The Ohio State University; Thomas Santner, The Ohio State University
8:55 AM
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Association Study of Children's Methylation and Growth Trajectory Using Functional Mixed Models
Colleen McKendry, North Carolina State University; Arnab Maity, North Carolina State University; Jung-Ying Tzeng, North Carolina State University
10:05 AM
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Analysis of dimension reduction in Gaussian process regression
Minyong Lee, Stanford University; Art Owen, Stanford University
11:00 AM
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Solution Uncertainty Quantification for Differential Equations
Oksana A Chkrebtii, The Ohio State University; David A Campbell, Simon Fraser University; Ben Calderhead, Imperial College London; Mark A Girolami, University of Warwick
11:00 AM
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Stabilizing Gradient Enhanced Emulators with Sparsity Constraints
Peter Qian, University of Wisconsin-Madison ; Jared Huling, University of Wisconsin-Madison
11:25 AM
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Multivariate Stochastic Process Models for Correlated Responses of Mixed Type
Tony Pourmohamad, Genentech; Herbert Lee, University of California, Santa Cruz
11:50 AM
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Exact Knowledge Gradient for Stochastic Computer Model Assisted Optimal Decision Making
QIONG ZHANG, Virginia Commonwealth University; Youngdeok Hwang , IBM Thomas J. Watson Research Center
2:05 PM
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Predicting Solar Irradiance as a Function of Location and Time: Multiple Model Calibration, Non-Stationarity, and Non-Space-Filling Design
Benjamin Haaland, Georgia Institute of Technology
2:25 PM
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Tukey Max-Stable Processes for Spatial Extremes
Ganggang Xu, Binghamton University; Marc G. Genton, KAUST
2:35 PM
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Model Calibration with Censored Data
Shan Ba, Procter & Gamble Company; Fang Cao, Georgia Institute of Technology; William Brenneman, The Procter & Gamble Company; Roshan Joseph Vengazhiyil, Georgia Institute of Technology
2:45 PM
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Thursday, 08/03/2017
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Bayesian Computing and Modeling for Nearest-Neighbor Gaussian Process Models
Sudipto Banerjee, UCLA Fielding School of Public Health
9:00 AM
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Estimating Heterogeneous Causal Effects: a Bayesian Nonparametric Approach
Xinyi Xu, Ohio State University; Ling Wang, Ohio State University; Bo Lu, The Ohio State University; Steven MacEachern, The Ohio State University
9:25 AM
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Practical Bayesian inference based on Nearest Neighbor Gaussian Processes (NNGP) model for massive spatial data
Lu Zhang, UCLA; Abhirup Datta, Johns Hopkins University; Sudipto Banerjee, UCLA Fielding School of Public Health
10:05 AM
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Joint Asymptotics for Estimating the Fractal Indices of Bivariate Gaussian Processes
Yuzhen Zhou, University of Nebraska-Lincoln; Yimin Xiao, Michigan State University
12:05 PM
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