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Theses/Project Reports from 2023

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Examining the Use of a Network Bypass to Circumvent Data Diodes Within Industrial Control Systems, Bryce Molesh

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Effects Of Concussion And Visuomotor Metrics On NHL Performance: An Explainable AI Approach, Michael T. Moschitto

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Smartphone Based Object Detection for Shark Spotting, Darrick W. Oliver

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An Empirical Evaluation of Neural Process Meta-Learners for Financial Forecasting, Kevin G. Patel

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Wasm-PBChunk: Incrementally Developing A Racket-To-Wasm Compiler Using Partial Bytecode Compilation, Adam C. Perlin

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Neural Tabula Rasa: Foundations for Realistic Memories and Learning, Patrick R. Perrine

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Simple Open-Source Formal Verification of Industrial Programs, Christopher Disney Peterson

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A Novel Approach to Extending Music Using Latent Diffusion, Keon Roohparvar and Franz J. Kurfess

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MMF-DRL: Multimodal Fusion-Deep Reinforcement Learning Approach with Domain-Specific Features for Classifying Time Series Data, Asmita Sharma

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Exploration of Semi-supervised Learning for Convolutional Neural Networks, Nicholas Sheffler

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Decentralized Machine Learning On Blockchain: Developing A Federated Learning Based System, Nikhil Sridhar

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Deep Learning Recommendations for the ACL2 Interactive Theorem Prover, Robert K. Thompson and Robert K. Thompson

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Play Area Utilization Optimization for Room-scale Exploration of Virtual Worlds, Chase VanderZwan

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Shelfaware: Accelerating Collaborative Awareness with Shelf CRDT, John C. Waidhofer

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Reinforcement Learning Framework For The Unreal Engine, Justin B. Wheeler