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1.
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.
4.
Large-Scale, Low-Latency State Estimation Of Cyberphysical Systems With An Application To Traffic Estimation
by Hunter, Timothy Jason, Ph.D.  University of California, Berkeley. 2014: 176 pages; 3686329.
5.
Connection between Graphical Potential Games and Markov Random Fields with an Extension to Bayesian Networks
by Wang, Shiyun, M.S.  California State University, Long Beach. 2018: 43 pages; 10785804.
6.
Efficient Markov Chain Monte Carlo Methods
by Fang, Youhan, Ph.D.  Purdue University. 2018: 107 pages; 10809188.
7.
Solving Large-Scale Inverse Problems via Approximate Message Passing and Optimization
by Ma, Yanting, Ph.D.  North Carolina State University. 2017: 180 pages; 10758823.
9.
A New Control Paradigm for Stochastic Differential Equations
by Schmid, Matthias J. A., Ph.D.  State University of New York at Buffalo. 2017: 310 pages; 10285670.
10.
Remote Homology Detection in Proteins Using Graphical Models
by Daniels, Noah Manus, Ph.D.  Tufts University. 2013: 122 pages; 3563611.
11.
Multimedia protection using content and embedded fingerprints
by Varna, Avinash Laxmisha, Ph.D.  University of Maryland, College Park. 2011: 208 pages; 3461319.
13.
Multi-Scale Movement of Demersal Fishes in Alaska
by Nielsen, Julie K., Ph.D.  University of Alaska Fairbanks. 2019: 278 pages; 13805849.
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16.
Efficient image restoration algorithms for near-circulant systems
by Pan, Ruimin, Ph.D.  Auburn University. 2007: 130 pages; 3265586.
17.
Random Linear Network Coding with Added Prefix Bits
by Mickey, Joshua, M.S.  University of Louisiana at Lafayette. 2017: 68 pages; 10682547.
18.
Inference Algorithms and Sensorimotor Representations in Brains and Machines
by Mudigonda, Mayur, Ph.D.  University of California, Berkeley. 2019: 154 pages; 13904872.
19.
Inversion of Rough-Surface Parameters via Polarimetric Synthetic Aperture Radar Data
by Lorenzo, Nicholas Angelo, Ph.D.  Rensselaer Polytechnic Institute. 2019: 212 pages; 27547649.
20.
Conditional modeling and conditional inference
by Chang, Lo-Bin, Ph.D.  Brown University. 2010: 199 pages; 3430173.
21.
Longitudinal Tissue Segmentation Methods for the Aging Brain
by Schwarz, Christopher George, Ph.D.  University of California, Davis. 2012: 148 pages; 3540732.
22.
Prediction for the Change of the Concentration of Radioactive Gas Using Particle Filtering Method
by Jiang, Yichen, M.S.  State University of New York at Binghamton. 2017: 88 pages; 10620833.
23.
Flexible imaging for capturing depth and controlling field of view and depth of field
by Kuthirummal, Sujit, Ph.D.  Columbia University. 2009: 155 pages; 3348435.
24.
Three Applications of Gaussian Process Modeling in Evaluation of Longevity Risk Management
by Risk, James Kenneth, Ph.D.  University of California, Santa Barbara. 2017: 245 pages; 10620897.
25.
Learning and inference algorithms for dynamical system models of dextrous motion
by Varadarajan, Balakrishnan, Ph.D.  The Johns Hopkins University. 2011: 169 pages; 3496153.
26.
Cellular Automata, Game of Life and Chance
by Alvandipour, Mehrdad, M.S.  Southern Illinois University at Edwardsville. 2017: 43 pages; 10615332.
27.
Joint Modeling of Longitudinal Count and Binary Data Using Latent Variable Approaches
by Jackson, John C., Ph.D.  The George Washington University. 2011: 123 pages; 3465423.
28.
Higher-order Random Walk Methods for Data Analysis
by Wu, Tao, Ph.D.  Purdue University. 2018: 135 pages; 10790747.
29.
Distinguishing signal from noise: New techniques for gravitational wave data analysis
by Baker, Paul Thomas, Ph.D.  Montana State University. 2013: 201 pages; 3596422.
30.
Dynamics and Information Processing in Recurrent Networks
by Kuczala, Alexander, Ph.D.  University of California, San Diego. 2019: 112 pages; 27541198.
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