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The classical paper list with code about generative adversarial nets
A Neuromodulated Meta-Learning algorithm
http://nlp.seas.harvard.edu/2018/04/03/attention.html
A every-so-often-updated collection of every causality + machine learning paper submitted to arXiv in the recent past.
Web interface for browsing, search and filtering recent arxiv submissions
BabyAI platform. A testbed for training agents to understand and execute language commands.
Essential Cheat Sheets for deep learning and machine learning researchers
Inferring and Executing Programs for Visual Reasoning
Notes for the Reinforcement Learning course by David Silver along with implementation of various algorithms.
Code for reproducing results in "Glow: Generative Flow with Invertible 1x1 Convolutions"
Representation learning on large graphs using stochastic graph convolutions.
Simple reference implementation of GraphSAGE.
Minimalistic gridworld package for OpenAI Gym
Assignments for CS294-112.
A platform for Applied Reinforcement Learning (Applied RL)
The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) paper in Pytorch.
ICLR Reproducibility Challenge 2019
Code for the paper "Improved Techniques for Training GANs"
Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)
Code for RL experiments in "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"
This is the companion curriculum to my guide to becoming a data scientist.
Mixed Incremental Cross-Entropy REINFORCE ICLR 2016
Code for the NeurIPS19 paper "Meta-Learning Representations for Continual Learning"
The Big-&-Extending-Repository-of-Transformers: Pretrained PyTorch models for Google's BERT, OpenAI GPT & GPT-2, Google/CMU Transformer-XL.
PyTorch Tutorial for Deep Learning Researchers
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Slides and exercises for the Deep Learning Summer School 2015 programming tutorials
Montréal Deep Learning Summer School 2016 material
Material for the Montréal Deep Learning Summer School 2017
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.