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neural-networks

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Geometric Dynamic Variational Autoencoders (GD-VAEs) for learning embedding maps for nonlinear dynamics into general latent spaces. This includes methods for standard latent spaces or manifold latent spaces with specified geometry and topology. The manifold latent spaces can be based on analytic expressions or general point cloud representations.

  • Updated Sep 23, 2025
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In this project, I explore various machine learning techniques including Principal Component Analysis (PCA), Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Sentiment Analysis in an effort to predict the directional changes in exchange rates for a list of developed and developing countries.

  • Updated Dec 5, 2022
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PlotNeuralNet is a Python package for generating high-quality neural network architecture diagrams using predefined or custom layer templates, seamlessly integrating Python and LaTeX. It includes pre-built resources for popular architectures like AlexNet and FCN, making it ideal for research papers and presentations.

  • Updated Dec 5, 2024
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