Look through the sections below:
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For general notes on physics informed/inverse physics informed neural networks (PINNS/IPINNS) click go to repository
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For more specific notes/codes on my Graduate Research with the Advanced Dynamics and Controls Laboratory at ERAU related to deep learning approaches towards physics informed human pilot behavior and physics informed pilot parameter estimation click go to repository .
- In this repo I have my notes on the problem formulations and analysis as well as links to view the google colab codes. The google colab links are the raw codes I use
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For Python machine learning codes that I used from coding tutorial online to learn, click go to repository.
- In this repo I went over the basics of Python (NumPy, Pandas, Matplotlib, Scit-kit Learn), Tensorflow (regression, classification), Pytorch (classificication, computer vision, building custom datasets/datalaoders for multiclass classification)
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For machine learning projects that use Scikit-Learn and TensorFlow click got to repository
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For Navigation and Controls related work click go to repository
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For related research papers used in reference to my graduate research click go to repository
Andrei, C., Stephen, B., & Hever, M. (2023, April). Performance Analysis of UAV Control Architectures Over Urban Environments with Degraded GNSS Accessibility. In 2023 IEEE/ION Position, Location and Navigation Symposium (PLANS) (pp. 67-74). IEEE.
Brutch, S., & Moncayo, H. (2024). Machine Learning Approach to Estimation of Human-Pilot Model Parameters. In AIAA SCITECH 2024 Forum (p. 1200).