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3.
Development of Multistep and Degenerate Variational Integrators for Applications in Plasma Physics
by Ellison, Charles Leland, Ph.D.  Princeton University. 2016: 272 pages; 10090246.
5.
Variational image segmentation based on pixel pairwise similarities
by Bertelli, Luca, Ph.D.  University of California, Santa Barbara. 2009: 192 pages; 3350379.
6.
Variational and Structural Methods in Mean Field Spin Glasses
by Jagannath, Aukosh Sundar, Ph.D.  New York University. 2016: 334 pages; 10139632.
7.
Comparison and Fine-Grained Analysis of Sequence Encoders for Natural Language Processing
by Keller, Thomas Anderson, M.S.  University of California, San Diego. 2017: 87 pages; 10599339.
8.
Symmetric Dual-Wind Discontinuous Galerkin Methods for Elliptic Variational Inequalities
by Rapp, Aaron Frost, Ph.D.  The University of North Carolina at Greensboro. 2020: 209 pages; 28001615.
9.
Variational Problems on Domains with Inclusions. Homogenization Through Γ-Convergence
by Gyrya, Vitaliy T., M.S.  The University of Akron. 2005: 71 pages; 10805831.
10.
Computational Analysis of Deformable Manifolds: From Geometric Modeling to Deep Learning
by Schonsheck, Stefan C., Ph.D.  Rensselaer Polytechnic Institute. 2020: 137 pages; 28001226.
11.
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.
12.
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.
13.
GPT-Free Sensitivity Analysis for Reactor Depletion and Analysis
by Kennedy, Christopher Brandon, Ph.D.  North Carolina State University. 2015: 233 pages; 3710730.
14.
Data assimilation experiments with a simple coupled ocean-atmosphere model
by Singleton, Tamara, Ph.D.  University of Maryland, College Park. 2011: 128 pages; 3478901.
15.
Methodology for Fleet Uncertainty Reduction with Unsupervised Learning
by Modarres, Ceena, M.S.  University of Maryland, College Park. 2016: 77 pages; 10253325.
16.
A Geometric Variational Problem on a Periodic Domain
by Smpokos, Konstantinos, Ph.D.  The George Washington University. 2020: 100 pages; 27831110.
18.
Analysis of mathematical models of electrostatically deformed elastic bodies
by Beckham, Jon Regan, Ph.D.  University of Delaware. 2008: 169 pages; 3291768.
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.
Bayesian lasso: An extension for genome-wide association study
by Joo, LiJin, Ph.D.  New York University. 2017: 119 pages; 10243856.
21.
A Total Variation and Spatially Varying Estimation Model for Image Restoration
by Hu, Xiaofei, Ph.D.  Syracuse University. 2010: 144 pages; 3459386.
22.
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.
23.
Quasi-Variational Inequalities for Source-Expanding Hele-Shaw Problems
by DeIonno, John Adrian, Ph.D.  University of California, Berkeley. 2013: 74 pages; 3593813.
25.
Micromechanics Based Failure Analysis of Heterogeneous Materials
by Sertse, Hamsasew M., Ph.D.  Purdue University. 2017: 176 pages; 10689831.
26.
On Identification of Nonlinear Parameters in PDEs
by Kahler, Raphael, M.S.  Rochester Institute of Technology. 2016: 80 pages; 10117725.
28.
Novel residual-based large eddy simulation turbulence models for incompressible magnetohydrodynamics
by Sondak, David, Ph.D.  Rensselaer Polytechnic Institute. 2013: 234 pages; 3601031.
29.
Nonconvex Min-Max Optimization in Deep Learning: Algorithms and Applications
by Liu, Mingrui, Ph.D.  The University of Iowa. 2020: 186 pages; 28031308.
30.
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