Based on their recent activity, Pedro Cuenca's current interest is in generative AI, specifically vector quantized variational autoencoders (VQ-VAE) as evidenced by their star of a PyTorch implementation.
Recent Activity
PyTorch implementation of VQ-VAE by Aäron van den Oord et al.
Highlights: This repository provides a PyTorch implementation of Vector Quantized Variational Autoencoder (VQ-VAE), a neural architecture that learns discrete latent representations for images. It demonstrates how to use vector quantization in the latent space to capture important features while maintaining reconstruction quality.
Worth reading: The implementation is clean and well-documented, making it an excellent educational resource for understanding how VQ-VAEs work and how to implement them in PyTorch.