Stars
MIT IAP short course: Matrix Calculus for Machine Learning and Beyond
This repo is meant to serve as a guide for Machine Learning/AI technical interviews.
The official implementation of Autoregressive Image Generation using Residual Quantization (CVPR '22)
🌲 Stanford CS 228 - Probabilistic Graphical Models
Deep probabilistic analysis of single-cell and spatial omics data
Implements sharpness-aware minimization (https://arxiv.org/abs/2010.01412) in TensorFlow 2.
This repository has scripts and other files that are part of the lecture notes and assignments of the course "Advanced Statistical Inference" taught at FME, UPC Barcelonatech.
Production infrastructure for machine learning at scale
Code for a dynamic multilevel Bayesian model to predict US presidential elections. Written in R and Stan.
Code for the paper "Language Models are Unsupervised Multitask Learners"
ChromDiff program as described in Yen and Kellis, Nature Communications 2015.
LeagueAI software framework for League of Legends that provides information about the state of the game based on Image Recognition using OpenCV and Pytorch.
An open implementation of Pure CFR applied to ACPC poker games.
Latex code for making neural networks diagrams
Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.
Finds the Nash equilibrium for river play in No Limit Texas Hold'Em
List of software packages for multi-omics analysis
A small library for automatical adjustment of text position in matplotlib plots to minimize overlaps.
Python and C++ code for reading and writing genomics data.
Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.
Resource of human chromosome schematics & images
A fast, efficient universal vector embedding utility package.
Generative Adversarial Networks implemented in PyTorch and Tensorflow
A scikit-learn compatible neural network library that wraps PyTorch
StarGAN - Official PyTorch Implementation (CVPR 2018)
This is the code for "Capsule Networks: An Improvement to Convolutional Networks" by Siraj Raval on Youtube
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.