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1.
Early Mammalian Neural Crest Development
by Betters, Erin Ann, Ph.D.  Yale University. 2012: 168 pages; 3535405.
3.
Transcriptional Regulation of the Developing Neural Crest in Xenopus
by Medina Ruiz, Sofia, Ph.D.  University of California, Berkeley. 2015: 135 pages; 10186646.
4.
Automated Feature Engineering for Deep Neural Networks with Genetic Programming
by Heaton, Jeff, Ph.D.  Nova Southeastern University. 2017: 201 pages; 10259604.
6.
Vagal neural crest cell patterning and migratory behavior
by Kuo, Bryan R., Ph.D.  University of California, Davis. 2010: 137 pages; 3404960.
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Novel patterns of activity in the hippocampus
by Kay, Kenneth, Ph.D.  University of California, San Francisco. 2016: 130 pages; 10133436.
10.
Variable Memory Recurrent Neural Networks for Nano Sat Launch Vehicle attitude control
by Sclafani, Rodolfo J., M.S.  California State University, Long Beach. 2014: 79 pages; 1527749.
11.
Utilizing Various Neural Network Architectures to Play a Game Developed for Human Players
by Arender, Blake, M.S.  The University of Mississippi. 2018: 51 pages; 10752390.
12.
A study of cell-based genetic algorithms with applications to neural networks
by Dinh, Hoa, M.S.  California State University, Long Beach. 2013: 62 pages; 1527480.
13.
Evaluation and Design of Robust Neural Network Defenses
by Carlini, Nicholas, Ph.D.  University of California, Berkeley. 2018: 138 pages; 10931076.
14.
Coordination of patterning and morphogenesis during early development in Xenopus laevis
by Thompson Exner, Cameron Ruth, Ph.D.  University of California, Berkeley. 2016: 108 pages; 10192543.
15.
Design of a Multi-objective Landing Trajectory Using Artificial Neural Networks
by Dedman, Phoebe Elizabeth, M.S.  California State University, Long Beach. 2018: 118 pages; 10837984.
16.
Nonlinear discriminant analysis based feature dimensionality reduction for automatic speech recognition
by Hu, Hongbing, Ph.D.  State University of New York at Binghamton. 2010: 145 pages; 3423029.
17.
Computational modeling of biological neural networks on GPUS: Strategies and performance
by Galbraith, Byron V., M.S.  Marquette University. 2010: 130 pages; 1479117.
18.
Machine Learning Applications to Robot Control
by Abdul-hadi, Omar, Ph.D.  University of California, Berkeley. 2018: 93 pages; 10817183.
19.
Gray-cast iron classification based on graphite flakes using image morphology and neural networks
by Yeliyur Siddegowda, Darshan, M.S.  California State University, Long Beach. 2016: 55 pages; 10017846.
20.
DiffFrameNet: A Deep Learning Method for Intuitive Robot Navigation
by Cao, Bo, M.S.  University of Colorado at Boulder. 2018: 69 pages; 10809457.
21.
BCAP: An Artificial Neural Network Pruning Technique to Reduce Overfitting
by Brantley, Kiante, M.S.  University of Maryland, Baltimore County. 2016: 71 pages; 10140605.
22.
Stochastic Neural Algorithms
by Engler, Gary Ronald, Jr., Ph.D.  Stevens Institute of Technology. 2018: 161 pages; 10979690.
24.
Using Neural Networks to Predict Vortex-Panel Analyses: A Feasibility Study
by Wright, Brendan, M.S.  Rensselaer Polytechnic Institute. 2018: 103 pages; 10980821.
27.
KLC1 deficiency alters APP and tau levels and impairs neuronal development
by Killian, Rhiannon Lynn, Ph.D.  University of California, San Diego. 2011: 138 pages; 3458477.
28.
An optogenetic brain-machine interface for spatiotemporal neuromodulation
by Baumgartner, Ryan, M.S.  The University of Wisconsin - Milwaukee. 2014: 97 pages; 1573289.
29.
Spiking Neural Networks and Sparse Deep Learning
by Tavanaei, Amirhossein, Ph.D.  University of Louisiana at Lafayette. 2018: 176 pages; 10807940.
30.
A General Purpose Neural Processor
by Mountain, David Jerome, Ph.D.  University of Maryland, Baltimore County. 2017: 171 pages; 10268058.
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