Must-read papers on graph neural networks (GNN)

Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"

Graph Neural Network Library for PyTorch

PyTorch DDPM implementation

This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.

Flax is a neural network library for JAX that is designed for flexibility.

JAX-based neural network library

Data and code for the paper "Co-citation and Co-authorhship Networks of Statisticians" (https://www.tandfonline.com/doi/full/10.1080/07350015.2021.1978469).

The github repository for our work, exploratory analysis of dynamic networks using latent functions

A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.

Fama French 3 Factor Model

Machine learning for Anonymous detection of an alcoholic by EEG signals

An R Package for Estimating Time-Varying Graphical Models

The Estimation and Inference for Dynamic Nonparanormal Graphical Models

A Package for Dynamic Graphical Model Estimation. Future versions in R coming soon

PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡

Install and Run Python Applications in Isolated Environments

Fast and Easy Infinite Neural Networks in Python

Understanding Deep Learning - Simon J.D. Prince

《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.