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1.
Development and Testing of a Combined Neural-Genetic Algorithm to Identify CO2 Sequestration Candidacy Wells
by Zhang, Xiaohui, M.S.  University of Louisiana at Lafayette. 2015: 140 pages; 1594272.
2.
Evaluation and Design of Robust Neural Network Defenses
by Carlini, Nicholas, Ph.D.  University of California, Berkeley. 2018: 138 pages; 10931076.
3.
Unsupervised Generative Capsule Neural Networks
by Serowik, Justin J., Master's  Stevens Institute of Technology. 2018: 29 pages; 13420362.
4.
Different Sampling Techniques in Neural Networks
by Micael, Deborah, M.S.  The George Washington University. 2021: 28 pages; 27738059.
5.
Drilling Hydraulics Optimization Using Neural Networks
by Wang, Yanfang, M.S.  University of Louisiana at Lafayette. 2014: 73 pages; 1592757.
6.
Learning in chaotic recurrent neural networks
by Sussillo, David C., Ph.D.  Columbia University. 2009: 134 pages; 3346497.
8.
Spiking Neural Networks and Sparse Deep Learning
by Tavanaei, Amirhossein, Ph.D.  University of Louisiana at Lafayette. 2018: 176 pages; 10807940.
9.
Leveraging Deep Neural Networks to Study Human Cognition
by Peterson, Joshua C., Ph.D.  University of California, Berkeley. 2018: 129 pages; 10930700.
10.
Attention to Deep Structure in Recurrent Neural Networks
by Sharpe, Spencer S., M.S.  University of Wyoming. 2017: 62 pages; 10619110.
11.
Noise, Quantization, and Priors in Neural Networks
by Anderson, Alexander G., Ph.D.  University of California, Berkeley. 2018: 87 pages; 10822107.
12.
BCAP: An Artificial Neural Network Pruning Technique to Reduce Overfitting
by Brantley, Kiante, M.S.  University of Maryland, Baltimore County. 2016: 71 pages; 10140605.
13.
Neural networks involved in eye movements in humans
by Gurler, Demet, Ph.D.  The University of Alabama at Birmingham. 2012: 233 pages; 3512264.
14.
Electroencephalogram classification by forecasting with recurrent neural networks
by Forney, Elliott M., M.S.  Colorado State University. 2011: 79 pages; 1503664.
15.
Using Neural Networks to Predict Vortex-Panel Analyses: A Feasibility Study
by Wright, Brendan, M.S.  Rensselaer Polytechnic Institute. 2018: 103 pages; 10980821.
16.
Computational modeling of biological neural networks on GPUS: Strategies and performance
by Galbraith, Byron V., M.S.  Marquette University. 2010: 130 pages; 1479117.
17.
Artificial Neural Networks in Public Policy: Towards an Analytical Framework
by Lee, Joshua A., Ph.D.  George Mason University. 2020: 353 pages; 27956419.
18.
Neural Networks for Modeling and Control of Particle Accelerators
by Edelen, Auralee Linscott, Ph.D.  Colorado State University. 2020: 269 pages; 28028770.
19.
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.
20.
Detection of Canine Bone Cancer Using Artificial Neural Networks
by Gorre, Naveena, M.S.  Southern Illinois University at Edwardsville. 2020: 70 pages; 27957796.
21.
Analysis of Keystroke Dynamics Algorithms with Feedforward Neural Networks
by Su, Gordon, M.E.  University of Connecticut. 2020: 49 pages; 28262948.
22.
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.
23.
Determining Relative Permeability of North American Sandstone Utilizing Artificial Neural Networks
by Hamblin, Spencer, M.S.  University of Louisiana at Lafayette. 2016: 63 pages; 10245198.
24.
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.
25.
Lithium-Ion Battery SOC Estimation Using Deep Learning Neural Networks
by Wang, Rui, M.S.  Rutgers The State University of New Jersey, School of Graduate Studies. 2019: 55 pages; 22624788.
26.
Automated Feature Engineering for Deep Neural Networks with Genetic Programming
by Heaton, Jeff, Ph.D.  Nova Southeastern University. 2017: 201 pages; 10259604.
27.
Representation Learning for Text: Transfer Learning, Decomposition, and Bias in Neural Networks
by Romanov, Alexey, Ph.D.  University of Massachusetts Lowell. 2019: 103 pages; 22624438.
28.
29.
Convolutional Neural Networks for EEG Signal Classification in Asynchronous Brain-Computer Interfaces
by Forney, Elliott M., Ph.D.  Colorado State University. 2019: 239 pages; 27544218.
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