labmlai/annotated_deep_learning_paper_implementations
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Each implementation is built with PyTorch and rendered on an interactive website displaying code alongside paper-derived explanations in a split-pane format. Beyond core architectures, the collection spans specialized techniques like Flash Attention for transformers, LLM.int8() quantization for efficient inference, and game-theoretic algorithms (CFR for poker), with active weekly updates across diverse domains from diffusion models to graph neural networks.
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