[D] Clean, self-contained PyTorch re-implementations of 50+ ML papers (GANs, diffusion, meta-learning, 3D)

This repository collects clean, self-contained PyTorch reference implementations of over 50 machine learning papers, spanning GANs, VAEs, diffusion models, meta-learning, representation learning, and 3D reconstruction.

The implementations aim to:

• Stay faithful to the original methods
• Minimize boilerplate while remaining readable
• Be easy to run and inspect as standalone files
• Reproduce key qualitative or quantitative results where feasible

Repository (open-source):
https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code

Interested in hearing where clean, self-contained implementations are sufficient for understanding and reproducing results, and where additional engineering or scale becomes unavoidable.