Keyword Search
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Keyword Search Criteria: Approximation returned 45 record(s)
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Sunday, 07/29/2018
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P-Value Estimation for the Risk Score of a Prediction Model
Heidi Chen, Vanderbilt University Medical Center; Ming Li, Case Western Reserve University; Huiyun Wu, St. Jude Children's Research Hospital; Yu Shyr, Vanderbilt University Medical Center
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Polynomial Based Approximate Probability Distributions
Chris Elrod, Baylor University; James Stamey, Baylor University
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Multi-Scale Vecchia Approximation of Gaussian Processes
Jingjie Zhang, Texas A&M University; Matthias Katzfuss, Texas A&M University
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Polynomial Based Approximate Probability Distributions
Chris Elrod, Baylor University; James Stamey, Baylor University
2:10 PM
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P-Value Estimation for the Risk Score of a Prediction Model
Heidi Chen, Vanderbilt University Medical Center; Ming Li, Case Western Reserve University; Huiyun Wu, St. Jude Children's Research Hospital; Yu Shyr, Vanderbilt University Medical Center
3:00 PM
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Multi-Scale Vecchia Approximation of Gaussian Processes
Jingjie Zhang, Texas A&M University; Matthias Katzfuss, Texas A&M University
3:10 PM
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Adjusting a Subject-Specific Timing of Event in Longitudinal Studies
Hyunkeun Cho, University of Iowa; Seonjin Kim, Miami University; Myunghee Lee, Weill Cornell Medical College
4:05 PM
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A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis
Yu Yue, Baruch College, CUNY; Amanda Mejia, Indiana University; David Bolin, Gothenburg University; Finn Lindgren, The University of Edinburgh; Martin A Lindquist, Johns Hopkins University
5:05 PM
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Monday, 07/30/2018
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Hierarchical-Block Conditioning Approximations for High-Dimensional Multivariate Normal Probabilities
Jian Cao, King Abdullah University of Science and Technology; Marc G Genton, King Abdullah University of Science and Technology; David E Keyes, King Abdullah University of Science and Technology; George Turkiyyah, King Abdullah University of Science and Technology
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A Probabilistic Tool for Assessing the Laplace Approximation: Review, Optimization, and GPU Implementation
Shaun McDonald, Simon Fraser University; David Campbell, Simon Fraser University
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Applications of Directional Inference
Andrew McCormack; Nancy Reid, University of Toronto; Sri-Amirthan Theivendran, University of Toronto; Nicola Sartori, University of Padua
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Approximate Inference for Large Non-Gaussian Spatial Data
Daniel Zilber, Texas A&M University; Matthias Katzfuss, Texas A&M University
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Combining Predictive Mean Matching with the Penalized Spline of Propensity Prediction Method When Performing Multiple Imputation
Jay Xu; Roee Gutman, Brown University
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Some Model-Building Tools for Gaussian Processes, Using an Approximate Form of the Restricted Likelihood
Maitreyee Bose, University of Washington; James S. Hodges, University of Minnesota; Sudipto Banerjee, UCLA School of Public Health
8:35 AM
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Approximate Inference for Large Non-Gaussian Spatial Data
Daniel Zilber, Texas A&M University; Matthias Katzfuss, Texas A&M University
9:10 AM
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Fully Nonparametric Methods for Partially Complete Clustered Data
Yue Cui, Department of Statistics
9:35 AM
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Variational Approximation for Importance Sampling
Xiao Su, University of Illinois at Urbana Champaign; Yuguo Chen, University of Illinois at Urbana-Champaign
9:50 AM
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Posterior Convergence and Coverage Aspects of Gaussian Process Approximations
Biraj Subhra Guha, Texas A & M University; Debdeep Pati, Texas A&M University
10:50 AM
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Optimization-Based Calibration of Simulation Input Models
Henry Lam, Columbia University; Aleksandrina Goeva, Broad Institute; Huajie Qian, Columbia University; Bo Zhang, IBM Research AI
11:35 AM
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Combining Predictive Mean Matching with the Penalized Spline of Propensity Prediction Method When Performing Multiple Imputation
Jay Xu; Roee Gutman, Brown University
11:50 AM
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Power Approximations for Reliability Test Designs
Rebecca Dickinson
2:05 PM
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Spatio-Temporal Models for Probabilistic Wind Vector Forecasting in Saudi Arabia
Amanda Lenzi, King Abdullah University of Science and Technology; Marc G Genton, King Abdullah University of Science and Technology
3:20 PM
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Covariances, Robustness, and Variational Bayes
Ryan Giordano; Tamara Broderick, Massachusetts Institute of Technology; Michael Jordan, UC Berkeley
3:25 PM
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Approximate L0-Penalized Estimation of Piecewise-Constant Signals on Graphs
Zhou Fan, Stanford University; Leying Guan, Stanford University
3:35 PM
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Tuesday, 07/31/2018
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Power and Type I Error Assessments on Methods to Size Binomial Endpoints Under Unequal Randomization Ratios
Rong Wang, Pfizer Inc
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Differentiable Approximations of Hidden Markov Models for Variational Bayesian Inference
Lun Yin, Duke Institute for Brain Sciences; John Pearson, Duke University
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Multi-Resolution Approximations of Gaussian Processes for Multivariate Spatial Data
Wenlong Gong, Texas A&M University
8:35 AM
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Differentiable Approximations of Hidden Markov Models for Variational Bayesian Inference
Lun Yin, Duke Institute for Brain Sciences; John Pearson, Duke University
10:45 AM
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Variational Hamiltonian Monte Carlo via Score Matching
Cheng Zhang, Fred Hutchinson Cancer Research Center
11:25 AM
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Statistical Inference for Online Learning and Stochastic Approximation via Hierarchical Incremental Gradient Descent
Weijie Su, University of Pennsylvania; Yuancheng Zhu, University of Pennsylvania
11:35 AM
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Bayesian Analysis of Multinomial Counts from Small Areas and Sub-Areas
Balgobin Nandram, Worcester Polytechnic Institute
11:35 AM
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Gaussian Variational Approximation for High-Dimensional State Space Models
Robert Kohn, Univ of New South Wales; Matias Quiroz , University of New South wales ; David J Nott, National University of Singapore
2:05 PM
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A Stochastic Second-Order Generalized Estimating Equations Approach for Estimating Association Parameters Under Informative Missingness
Tom Chen; Eric Tchetgen Tchetgen, Harvard University; Rui Wang, Harvard Pilgrim HealthCare Institute
2:45 PM
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Wednesday, 08/01/2018
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A General Framework for Vecchia Approximations of Gaussian Processes
Matthias Katzfuss, Texas A&M University; Joseph Guinness, North Carolina State University
9:05 AM
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Examining Non-Stationarity in Spatial Processes via an M-RA and Mixture Priors
Veronica J. Berrocal, University of Michigan
10:05 AM
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Optimal Estimation of Simultaneous Signals Using Absolute Inner Product with Applications to Integrative Genomics
Rong Ma, University of Pennsylvania; Tianwen Cai, University of Pennsylvania; Hongzhe Li, University of Pennsylvania; Mark G Low, University of Pennsylvania
10:35 AM
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Efficient Estimation for Non-Stationary Spatial Covariance Functions with Application to High-Resolution Climate Model Emulation
Yuxiao Li, KAUST; Ying Sun, KAUST
11:35 AM
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Prediction of Melanoma Prognosis Class Using a Multiclass Discriminant Analysis Classifier with Variable Selection
Sarah Romanes, The University of Sydney; John T Ormerod, University of Sydney; Jean Yee Hwa Yang, University of Sydney, Australia
11:35 AM
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New Computational Methods for Non/Semiparametric Quantile Regression Models
Bo Kai, College of Charleston; Mian Huang, Shanghai University of Finance and Economics; Weixin Yao, University of California, Riverside; Yuexiao Dong, Temple University
3:20 PM
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Thursday, 08/02/2018
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Epsilon-Approximations to the Pitman-Yor Process
Pierpaolo De Blasi, University of Turin
8:35 AM
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Variational Inference for Proportional Hazards Model with Power Prior in Oncology Studies
Bo Jin, Boston Biomedical Inc.; Yue Chang, Boston Biomedical Inc
8:35 AM
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An Approximation to the Information Matrix of Hidden Markov Model
Qing Ji, University of Maryland, Baltimore County; Andrew Raim, U.S. Census Bureau; Nagaraj Neerchal, University of Maryland, Baltimore County
9:50 AM
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Global Mean-Field Variational Bayes for Density Regression
Tommaso Rigon, Bocconi University; Daniele Durante, Bocconi University
9:55 AM
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Bayesian Logistic Regression Model for Sub-Areas
Lu Chen, Worcester Polytechnic Institute; Balgobin Nandram, Worcester Polytechnic Institute
10:50 AM
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Efficient and Principled Score Estimation
Arthur Gretton, UCL
11:25 AM
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