annotated_deep_learning_paper_implementations/readme.md

LabML Neural Networks

This is a collection of simple PyTorch implementation of various neural network architectures and layers. We will keep adding to this.

Modules

✨ Transformers

Transformers module contains implementations for multi-headed attention and relative multi-headed attention.

• kNN-LM: Generalization through Memorization

✨ Recurrent Highway Networks

✨ LSTM

✨ Capsule Networks

✨ Generative Adversarial Networks

• GAN with a multi-layer perceptron
• GAN with deep convolutional network
• Cycle GAN

✨ Sketch RNN

✨ Reinforcement Learning

• Proximal Policy Optimization with Generalized Advantage Estimation
• Deep Q Networks with with Dueling Network, Prioritized Replay and Double Q Network.

Installation

pip install labml_nn

Citing LabML

If you use LabML for academic research, please cite the library using the following BibTeX entry.

@misc{labml,
 author = {Varuna Jayasiri, Nipun Wijerathne},
 title = {LabML: A library to organize machine learning experiments},
 year = {2020},
 url = {https://lab-ml.com/},
}