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ai-safety-gridworlds

alphagozero-python-tensorflow

Congratulation to DeepMind! This is a reengineering implementation (on behalf of many other git repo in /support/) of DeepMind's Oct19th publication: [Mastering the Game of Go without Human Knowledge]. The supervised learning approach is more practical for individuals. (This repository has single purpose of education only)

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

captum

Model interpretability and understanding for PyTorch

deepvariant

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

detectron2

Detectron2 is FAIR's next-generation research platform for object detection and segmentation.

fast-style-transfer

TensorFlow CNN for fast style transfer ⚡🖥🎨🖼

github-slideshow

A robot powered training repository :robot:

github-upload

hca-jamboree-sampling

models

Implementation of models that couple VAEs with density estimation

nyc-traffic-analysis

occlusion-handling

Instance segmentation models for images with intense occlusion.

poincare-embeddings

PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"

pytorch-project-template

A scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinforcement Learning.

summarize-from-feedback

Code for "Learning to summarize from human feedback"

swift-algorithms

Swift Algorithms is an open-source package of sequence and collection algorithms, along with their related types.

tag-peek.vim

A neovim plugin for peeking at tag definitions using the `nvim_open_win` "floating window" feature.

training-kit

Open source on demand courses and cheat sheets for Git and GitHub

unet

unet for image segmentation

unet-image-segmentation

An implementation of the U-Net architecture for image segmentation

yolact

A simple, fully convolutional model for real-time instance segmentation.