NA2Q

??? 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, ... ?

A game theoretic approach to explain the output of any machine learning model.

Natural Language Processing Tutorial for Deep Learning Researchers

? Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.???

A PyTorch implementation of the Transformer model in "Attention is All You Need".

该仓库主要记录 NLP 算法工程师相关的顶会论文研读笔记

Scenic: A Jax Library for Computer Vision Research and Beyond

? Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!

Algorithms for explaining machine learning models