Google's differential privacy libraries.

Paxos Made Moderately Complex

The book Distributed systems: for fun and profit

PyTorch code accompanying our paper on Maximum Entropy Generators for Energy-Based Models

Noise Conditional Score Networks (NeurIPS 2019, Oral)

Must-read papers on graph neural networks (GNN)

A digital currency for a new era of decentralized trust

PyTorch implementations of algorithms for density estimation

Real NVP PyTorch a Minimal Working Example | Normalizing Flow

disentanglement_lib is an open-source library for research on learning disentangled representations.

Library for training machine learning models with privacy for training data

Chebfun: numerical computing with functions.

Implementation of Conditional Generative Adversarial Networks in PyTorch

Simple Implementation of many GAN models with PyTorch.

Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

Pytorch implementation of Self-Attention Generative Adversarial Networks (SAGAN)

Implementation of Self-Attention Generative Adversarial Networks by Zhang et al. (with spectral normalization and projection discriminator)

🖥️ CS446: Machine Learning in Spring 2018, University of Illinois at Urbana-Champaign

Network Alignment Codes in Julia

Graph and Network algorithms in Julia

Munkres algorithm for the optimal assignment problem

source code of the paper Graphical Generative Adversarial Networks

The Hitchiker's Guide to PyTorch

Sliced Wasserstein Generator

A list of all named GANs!

A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility

Graph Neural Network Library for PyTorch

Code and model for the paper "Improving Language Understanding by Generative Pre-Training"

Code accompanying the paper "Learning Permutations with Sinkhorn Policy Gradient"

Cool links & research papers related to Machine Learning applied to source code (MLonCode)