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1.
Bayesian lasso: An extension for genome-wide association study
by Joo, LiJin, Ph.D.  New York University. 2017: 119 pages; 10243856.
2.
Methodology for Fleet Uncertainty Reduction with Unsupervised Learning
by Modarres, Ceena, M.S.  University of Maryland, College Park. 2016: 77 pages; 10253325.
4.
Nonparametric Bayes: Inference under nonignorable missingness and model selection
by Linero, Antonio, Ph.D.  University of Florida. 2015: 147 pages; 10299009.
5.
Latent Variable Modeling for Networks and Text: Algorithms, Models and Evaluation Techniques
by Foulds, James Richard, Ph.D.  University of California, Irvine. 2014: 287 pages; 3631094.
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Computational methods for support vector machine classification and large-scale Kalman filtering
by Howard, Marylesa Marie, Ph.D.  University of Montana. 2013: 124 pages; 3568109.
8.
Signatures of Approximate Bayesian Inference in Early Visual Perception
by Lange, Richard D., Ph.D.  University of Rochester. 2020: 360 pages; 28093511.
9.
Hierarchical Bayes estimation and empirical best prediction of small-area proportions
by Liu, Benmei, Ph.D.  University of Maryland, College Park. 2009: 223 pages; 3359401.
10.
Variational image segmentation based on pixel pairwise similarities
by Bertelli, Luca, Ph.D.  University of California, Santa Barbara. 2009: 192 pages; 3350379.
11.
Semi-Supervised Learning for Electronic Phenotyping in Support of Precision Medicine
by Halpern, Yonatan, Ph.D.  New York University. 2016: 353 pages; 10192124.
12.
Application of a Hidden Bayes Naïve Multiclass Classifier in Network Intrusion Detection
by Koc, Levent, Ph.D.  The George Washington University. 2013: 146 pages; 3546303.
13.
Development of Multistep and Degenerate Variational Integrators for Applications in Plasma Physics
by Ellison, Charles Leland, Ph.D.  Princeton University. 2016: 272 pages; 10090246.
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Towards Effective and Controllable Neural Text Generation
by Fang, Le, Ph.D.  State University of New York at Buffalo. 2020: 88 pages; 27994869.
17.
Objective Bayesian inference for stress-strength models and Bayesian ANOVA
by Min, Xiaoyi, Ph.D.  University of Missouri - Columbia. 2012: 128 pages; 3537873.
18.
Variational and Structural Methods in Mean Field Spin Glasses
by Jagannath, Aukosh Sundar, Ph.D.  New York University. 2016: 334 pages; 10139632.
19.
Static Randall-Sundrum Black Holes From a Variational Principle
by Fraser, Scott T., Ph.D.  University of California, Santa Barbara. 2010: 230 pages; 3427999.
20.
Quasi-Variational Inequalities for Source-Expanding Hele-Shaw Problems
by DeIonno, John Adrian, Ph.D.  University of California, Berkeley. 2013: 74 pages; 3593813.
21.
A Geometric Variational Problem on a Periodic Domain
by Smpokos, Konstantinos, Ph.D.  The George Washington University. 2020: 100 pages; 27831110.
23.
Variational Problems on Domains with Inclusions. Homogenization Through Γ-Convergence
by Gyrya, Vitaliy T., M.S.  The University of Akron. 2005: 71 pages; 10805831.
24.
Variational Monte Carlo Methods for Strongly Correlated Quantum Systems on Multileg Ladders
by Block, Matthew S., Ph.D.  University of California, Santa Barbara. 2011: 167 pages; 3473722.
25.
Using Social Dynamics to Make Individual Predictions: Variational Inference with Stochastic Kinetic Model
by Xu, Zhen, Ph.D.  State University of New York at Buffalo. 2016: 118 pages; 10253123.
29.
Active Collaborative Planning and Sensing in Human-Robot Teams
by Burks, Charles Luke, Ph.D.Eng.  University of Colorado at Boulder. 2020: 181 pages; 28031373.
30.
Data assimilation experiments with a simple coupled ocean-atmosphere model
by Singleton, Tamara, Ph.D.  University of Maryland, College Park. 2011: 128 pages; 3478901.
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