Neural Networks and Deep Learning

An exploration of neural network-based deep learning, finding methods for classification, regression, and generative modelling.

Contents extracted from academic work:

1. Projecting 3D Gaussian Data onto a Unit Sphere Using Deep Learning
2. Classification of Rotated MNIST Digits using Convolutional Neural Networks
3. Generative Modelling of Shapes using Variational Autoencoders
4. Generative Modelling of 2D Distributions using Flow Matching and Score Matching: A Comparative Study