VortexNet: Neural network based on fluid dynamics

The article introduces VortexNet, a neural network model inspired by fluid dynamics, with toy implementations available in a repository. These examples showcase the integration of PDE-based vortex layers and fluid-inspired mechanisms into neural architectures like autoencoders for various datasets. The provided scripts demonstrate building and training a VortexNet Autoencoder on the MNIST dataset and custom image datasets, offering features like data augmentation and latent space interpolation. Users can access the code repository, install dependencies, prepare data, and run the scripts for experimenting with VortexNet models.