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1.
Conditional modeling and conditional inference
by Chang, Lo-Bin, Ph.D.  Brown University. 2010: 199 pages; 3430173.
2.
Geometric representations and deep Gaussian conditional random field networks for computer vision
by Vemulapalli, Raviteja, Ph.D.  University of Maryland, College Park. 2016: 185 pages; 10192530.
3.
Robust network inference with multivariate t-distributions
by Finegold, Michael A., Ph.D.  The University of Chicago. 2010: 94 pages; 3419771.
4.
The Method of Batch Inference for Multivariate Diffusions
by Lysy, Martin, Ph.D.  Harvard University. 2012: 120 pages; 3495622.
5.
Information theoretic approaches towards regulatory network inference
by Chaitankar, VIjender, Ph.D.  Virginia Commonwealth University. 2012: 125 pages; 3550865.
6.
Efficient inference algorithms for near-deterministic systems
by Chatterjee, Shaunak, Ph.D.  University of California, Berkeley. 2013: 130 pages; 3616611.
7.
Randomization inference and principal stratification in HIV prevention studies
by Nolen, Tracy L., Dr.P.H.  The University of North Carolina at Chapel Hill. 2012: 111 pages; 3512798.
9.
Nonparametric Bayes: Inference under nonignorable missingness and model selection
by Linero, Antonio, Ph.D.  University of Florida. 2015: 147 pages; 10299009.
10.
Latent Variable Modeling and Causal Inference in Population-Structured Genetics
by Cabreros, Irineo C., Ph.D.  Princeton University. 2020: 219 pages; 27546470.
13.
Generalized fiducial inference for mixed linear models
by Cisewski, Jessica, Ph.D.  The University of North Carolina at Chapel Hill. 2012: 151 pages; 3512608.
14.
Computational inference of genetic regulatory networks in human cancer cells
by Margolin, Adam Arne, Ph.D.  Columbia University. 2008: 282 pages; 3299359.
15.
Statistical inference procedure for step-stress accelerated life testing models
by Lee, Jinsuk, Ph.D.  Arizona State University. 2008: 113 pages; 3338480.
17.
Performance analysis and inference of communication networks
by Ni, Jian, Ph.D.  Yale University. 2008: 178 pages; 3342752.
18.
Unsupervised linguistic inference
by Lamar, Michael T., Ph.D.  Brown University. 2010: 165 pages; 3430192.
19.
Frameworks for Univariate and Multivariate Non-Stationary Analysis of Climatic Extremes
by Cheng, Linyin, Ph.D.  University of California, Irvine. 2014: 151 pages; 3642917.
20.
Heterogeneous Treatment Effect Estimation Using Machine Learning
by Kuenzel, Soeren R., Ph.D.  University of California, Berkeley. 2019: 177 pages; 13903254.
22.
Program inconsistency detection: Universal reachability analysis and conditional slicing
by Tomb, Aaron, Ph.D.  University of California, Santa Cruz. 2011: 182 pages; 3471818.
23.
Learning and inference algorithms for dynamical system models of dextrous motion
by Varadarajan, Balakrishnan, Ph.D.  The Johns Hopkins University. 2011: 169 pages; 3496153.
24.
Topics in model-based population inference
by Schutt, Rachel, Ph.D.  Columbia University. 2010: 158 pages; 3400625.
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.
26.
Causal models in prediction and diagnosis
by Fernbach, Philip M., Ph.D.  Brown University. 2010: 157 pages; 3430132.
27.
Deep Learning for Attribute Inference, Parsing, and Recognition of Face
by Luo, Ping, Ph.D.  The Chinese University of Hong Kong (Hong Kong). 2014: 122 pages; 3691916.
29.
Bayesian Nonparametric Methods for Analysis of Electronic Health Records
by Xu, Dandan, Ph.D.  University of Florida. 2016: 108 pages; 10679207.
30.
Objective Bayesian inference for stress-strength models and Bayesian ANOVA
by Min, Xiaoyi, Ph.D.  University of Missouri - Columbia. 2012: 128 pages; 3537873.
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