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labmlai/annotated_deep_learning_paper_implementations

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
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labml.ai Deep Learning Paper Implementations

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.

Screenshot

We are actively maintaining this repo and adding new implementations almost weekly. Twitter for updates.

Paper Implementations

✨ Transformers

✨ Eleuther GPT-NeoX

✨ Diffusion models

✨ Generative Adversarial Networks

✨ Recurrent Highway Networks

✨ LSTM

✨ HyperNetworks - HyperLSTM

✨ ResNet

✨ ConvMixer

✨ Capsule Networks

✨ U-Net

✨ Sketch RNN

✨ Graph Neural Networks

✨ Counterfactual Regret Minimization (CFR)

Solving games with incomplete information such as poker with CFR.

✨ Reinforcement Learning

✨ Optimizers

✨ Normalization Layers

✨ Distillation

✨ Adaptive Computation

✨ Uncertainty

✨ Activations

✨ Langauge Model Sampling Techniques

✨ Scalable Training/Inference

Highlighted Research Paper PDFs

Installation

pip install labml-nn

Citing

If you use this for academic research, please cite it using the following BibTeX entry.

@misc{labml,
 author = {Varuna Jayasiri, Nipun Wijerathne},
 title = {labml.ai Annotated Paper Implementations},
 year = {2020},
 url = {https://nn.labml.ai/},
}

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