Explore and learn from PyTorch implementations of significant deep learning papers.
This repository provides over 60 well-annotated PyTorch implementations of influential deep learning research papers, including transformers, GANs, and reinforcement learning algorithms. Each implementation is accompanied by clear explanations and often includes side-by-side notes for deeper understanding, making complex topics more accessible.
Explore and learn from PyTorch implementations of significant deep learning papers.
Deep learning practitioners, researchers, and students looking to understand and replicate foundational AI models.
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This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations,
The website renders these as side-by-side formatted notes. We believe these would help you understand these algorithms better.
We are actively maintaining this repo and adding new
implementations almost weekly.
