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1.
Learning in chaotic recurrent neural networks
by Sussillo, David C., Ph.D.  Columbia University. 2009: 134 pages; 3346497.
2.
Attention to Deep Structure in Recurrent Neural Networks
by Sharpe, Spencer S., M.S.  University of Wyoming. 2017: 62 pages; 10619110.
3.
Electroencephalogram classification by forecasting with recurrent neural networks
by Forney, Elliott M., M.S.  Colorado State University. 2011: 79 pages; 1503664.
4.
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.
5.
Dynamics and Information Processing in Recurrent Networks
by Kuczala, Alexander, Ph.D.  University of California, San Diego. 2019: 112 pages; 27541198.
6.
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.
7.
Spacecraft Formation Control: Adaptive PID-Extended Memory Recurrent Neural Network Controller
by Gonzalez, Juan, M.S.  California State University, Long Beach. 2018: 76 pages; 10978237.
9.
Learning temporal representations in cortical networks through reward dependent expression of synaptic plasticity
by Gavornik, Jeffrey Peter, Ph.D.  The University of Texas at Austin. 2009: 121 pages; 3360319.
10.
Noise, Quantization, and Priors in Neural Networks
by Anderson, Alexander G., Ph.D.  University of California, Berkeley. 2018: 87 pages; 10822107.
11.
Control of a Three-Phase NPC Inverter Using Model Predictive Control and an Long Short-Term Memory Recurrent Neural Network
by Ashbaugh, Daniel L., M.S.  Southern Illinois University at Edwardsville. 2020: 144 pages; 27957425.
13.
Automated Feature Engineering for Deep Neural Networks with Genetic Programming
by Heaton, Jeff, Ph.D.  Nova Southeastern University. 2017: 201 pages; 10259604.
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15.
Text Representation using Convolutional Networks
by Zhang, Xiang, Ph.D.  New York University. 2019: 164 pages; 10928487.
16.
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.
17.
Evaluation and Design of Robust Neural Network Defenses
by Carlini, Nicholas, Ph.D.  University of California, Berkeley. 2018: 138 pages; 10931076.
18.
Predicting Tropical Cyclone Intensity from Geosynchronous Satellite Images Using Deep Neural Networks
by Udumulla, Niranga Mahesh, M.S.  Florida Atlantic University. 2020: 112 pages; 28262639.
19.
Deep Networks for Forward Prediction and Planning
by Henaff, Mikael, Ph.D.  New York University. 2018: 164 pages; 10928805.
20.
Computational modeling of biological neural networks on GPUS: Strategies and performance
by Galbraith, Byron V., M.S.  Marquette University. 2010: 130 pages; 1479117.
21.
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.
22.
Neural Networks for Modeling and Control of Particle Accelerators
by Edelen, Auralee Linscott, Ph.D.  Colorado State University. 2020: 269 pages; 28028770.
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24.
Decoding the rhythms of avian auditory LFP
by Schachter, Mike J., Ph.D.  University of California, Berkeley. 2016: 53 pages; 10192590.
25.
Short-Term Traffic Delay Prediction at the Niagara Frontier Border Crossings Using Deep Learning
by Chauhan, Rishabh Singh, M.S.  State University of New York at Buffalo. 2019: 154 pages; 13882472.
26.
Classification of Faults in Microgrids Using Deep Learning
by Karan, Sainesh, M.S.  California State University, Long Beach. 2020: 74 pages; 27834650.
27.
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.
28.
Representation Learning on Sequential Medical Data
by Hyland, Stephanie L., Ph.D.  Weill Medical College of Cornell University. 2019: 245 pages; 13805668.
29.
The Structure and Dimension of Variability Across Multi-Area Cortical Circuits
by Rager, Danielle Marie, Ph.D.  Carnegie Mellon University. 2020: 133 pages; 27994202.
30.
Learning from Temporally-Structured Human Activities Data
by Lipton, Zachary C., Ph.D.  University of California, San Diego. 2017: 274 pages; 10683703.
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