Keyword Search
Sessions Were Renumbered as of May 19.
Legend:
CC-W = McCormick Place Convention Center, West Building, CC-N = McCormick Place Convention Center, North Building
H = Hilton Chicago, UC= Conference Chicago at University Center
* = applied session ! = JSM meeting theme
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Keyword Search Criteria: Gaussian process returned 37 record(s)
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Monday, 08/01/2016
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Period Estimation for Sparsely Sampled Quasi-Periodic Functions: Application to Mira Variable Stars
Shiyuan He, Texas A&M University
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Secrets of the Dark Universe
Katrin Heitmann
8:35 AM
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Regression-Based Covariance Functions for Nonstationary Spatial Modeling
Mark Risser, Lawrence Berkeley National Laboratory
9:15 AM
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A Flexible Joint Longitudinal-Survival Model for Quantifying the Association Between Serum Biomarkers and Mortality
Daniel Gillen, University of California at Irvine; Sepehr Arkhavan, University of California at Irvine; Babak Shahbaba, University of California at Irvine
9:25 AM
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Period Estimation for Sparsely Sampled Quasi-Periodic Functions: Application to Mira Variable Stars
Shiyuan He, Texas A&M University
9:30 AM
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Optimal Bayes Classifiers for Functional Data and Density Ratios
Xiongtao Dai, Healthy Birth, Growth and Development knowledge integration (HBGDki) Community; Hans-Georg Mueller, University of California at Davis; Fang Yao, University of Toronto
10:50 AM
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DPOAE Test-Retest Difference Curves via Hierarchical Gaussian Processes
Timothy Hanson, University of South Carolina; Junshu Bao, University of South Carolina; Garnett McMillan, National Center for Rehabilitative Auditory Research; Kristin Knight, National Center for Rehabilitative Auditory Research
2:05 PM
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Using Computer Experiments and Gaussian Process Emulation to Facilitate Bayesian Optimal Design for Physical Models Derived from Ordinary Differential Equations
David Woods, University of Southampton; Antony Overstall, University of Glasgow; Benjamin Parker, University of Southampton
2:55 PM
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Stochastic Simulation of Predictive Space-Time Scenarios of Wind Speed Using Observations and Physical Models
Julie Bessac, Argonne National Lab; Emil Mihai Constantinescu, Argonne National Lab; Mihai Anitescu, Argonne National Lab
3:05 PM
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Bayesian Single Index Models
Kumaresh Dhara, Florida State University; Debajyoti Sinha, Florida State University; Debdeep Pati, Florida State University
3:20 PM
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Tuesday, 08/02/2016
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Combining Multivariate Stochastic Process Models with Filter Methods for Constrained Optimization
Tony Pourmohamad, University of California at Santa Cruz; Herbie Lee, University of California at Santa Cruz
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A Bayesian Hierarchical Data Fusion Approach Leveraging Lidar and Hyperspectral Remote Sensing Information to Improve Aboveground Forest Carbon Estimation for Interior Alaska, USA
Chad Babcock, University of Washington
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Bayesian Structural Mean Models
Bret Zeldow, University of Pennsylvania; Jason Roy, University of Pennsylvania
9:55 AM
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Advances of Bayesian Nonparametrics in Population Genetics of Infectious Diseases
Vladimir Minin, University of Washington
11:35 AM
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Spatial Prediction of Naturally Occurring Indoor Gamma Radiation Dose Rates in Great Britain
Mark Peter Little, National Cancer Institute; Pavel Chernyavskiy, National Cancer Institute; Gerald M. Kendall, University of Oxford; Philip S. Rosenberg, National Cancer Institute; Richard Wakeford, University of Manchester
2:05 PM
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Wednesday, 08/03/2016
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Time Series Matching for Novelty Detection in the Stepdown Ward: A Gaussian Process Approach
Glen Wright Colopy, University of Oxford; Marco A. F. Pimentel; Stephen J. Roberts; David A. Clifton
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A New Class of Nonseparable Bayesian Hierarchical Spatial Modeling for Sparse Gaussian Processes
Bledar Konomi, University of Cincinnati
9:20 AM
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Bayesian Network-Response Regression
Lu Wang, Duke University; Daniele Durante, University of Padua; David Dunson, Duke University
9:35 AM
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Bayesian Registration of Functions with a Gaussian Process Prior
Yi Lu, The Ohio State University; Sebastian A. Kurtek, The Ohio State University; Radu Herbei, The Ohio State University
9:50 AM
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Multi-Resolution Approaches for Big Spatial Data
Matthias Katzfuss, Texas A&M University
9:55 AM
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Free Lunches with Sparse Bayesian Nonparametric Learning: A Probabilistic Exploration of Lower Dimensional Structure Discovery with Sparse High-Dimensional Data
Anjishnu Banerjee, Medical College of Wisconsin
10:05 AM
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Gaussian Process Emulator-Based Inference for Spatial Models of Infectious Disease Systems
Rob Deardon, University of Calgary; Gyanendra Pokharel, University of Calgary
11:15 AM
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Variable Selection for Gaussian Process Models Using Experimental Design-Based Subagging
Yibo Zhao, Rutgers University; Ying Hung, Rutgers University
11:20 AM
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Approximate Likelihood Methods for Estimation and Prediction in Gaussian Process Regression Models for Computer Experiments
Ryan Parker, SAS Institute; Brian J. Reich, North Carolina State University; Chris Gotwalt, SAS Institute
11:35 AM
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Computational Enhancements to Bayesian Design of Experiments Using Gaussian Processes
Brian Phillip Weaver, Los Alamos National Laboratory
11:50 AM
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Bayesian Nonparametric Estimation for Dynamic Treatment Regimes with Sequential Transition Times
Peter F. Thall, MD Anderson Cancer Center; Yanxun Xu; Peter Mueller, The University of Texas at Austin; Abdus S. Wahed, University of Pittsburgh
2:05 PM
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Computational Considerations for Applying Nearest Neighbor Gaussian Processes to Large Spatial Data Sets: A Case Study from Forest Biomass Prediction Across Alaska
Sudipto Banerjee, University of California at Los Angeles; Abhirup Datta, University of Minnesota; Bruce Cook, NASA; Andrew Finley, Michigan State University
2:05 PM
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Flexible Link Functions in Nonparametric Binary Regression with Gaussian Process Priors
Xia Wang, University of Cincinnati; Dan Li, University of Cincinnati; Lizhen Lin, The University of Texas; Dipak Dey, University of Connecticut
2:05 PM
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Some Scalable Spatial Modeling Framework for Large Spatial Data
RAJARSHI GUHANIYOGI, University of California at Santa Cruz; Sudipto Banerjee, University of California at Los Angeles
2:30 PM
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Generalized Difference in Difference Models with Gaussian Processes
William Herlands, Carnegie Mellon University; Daniel B. Neill, Carnegie Mellon University; Akshaya Jha, Carnegie Mellon University; Seth Flaxman, University of Oxford; Kun Zhang, Carnegie Mellon University
2:35 PM
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Thursday, 08/04/2016
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Asymptotic Analysis of Covariance Parameter Estimation for Gaussian Processes in the Misspecified Case
Francois Bachoc, University Paul Sabatier
8:50 AM
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Degradation and Maintenance Modeling Using the Inverse Gaussian Process
Bo Henry Lindqvist, Norwegian University of Science and Technology; Odd Eirik Farestveit, Accenture
8:55 AM
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Ice Sheet Model Calibration with Paleoclimate and Modern Data
Murali Haran, Penn State University; Won Chang, Penn State University; David Pollard, Penn State University Earth and Environmental Systems Institute; Patrick Applegate, Penn State University
11:25 AM
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Inference for Multi-Model Ensembles: An Application in Glaciology
Derek Bingham, Simon Fraser University; Ofir Harari, Simon Fraser University; Gwenn Flowers, Simon Fraser University
11:50 AM
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