jparkerholder Goto Github PK
Name: Jack Parker-Holder
Type: User
Bio: Research Scientist at DeepMind
Twitter: jparkerholder
Blog: jparkerholder.github.io
Name: Jack Parker-Holder
Type: User
Bio: Research Scientist at DeepMind
Twitter: jparkerholder
Blog: jparkerholder.github.io
Code to run the ASEBO algorithm from the paper: From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization... please get in touch if interested!!
๐ง ๐ผ
bsuite is a collection of carefully-designed experiments that investigate core capabilities of a reinforcement learning (RL) agent
Continual reinforcement learning baselines: experiment specifications, implementation of existing methods, and common metrics. Easily extensible to new methods.
Using data mining techniques to classify small cap equity returns
This will serve as the public forum repository to which anyone can post. [Don't put your graded homework here!]
Deep Neuroevolution
Mastering Atari with Discrete World Models
Code from the paper "Effective Diversity in Population Based Reinforcement Learning", presented as a spotlight at NeurIPS 2020. This is the Evolution Strategies implementation, but of course the method can be used for gradient based RL algorithms (e.g. TD3).
Simple ES implementation using ray and numpy
Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning
๐ด OffCon^3: SOTA PyTorch SAC and TD3 Implementations (arxiv: 2101.11331)
Code for the Population-Based Bandits Algorithm, presented at NeurIPS 2020.
tutorial notebooks
Materials for the 2017 QMSS Python Workshop
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
๐ Codebase for the ICML '20 paper "Ready Policy One: World Building Through Active Learning" (arxiv: 2002.02693)
A list of papers regarding generalization in (deep) reinforcement learning
๐งถ Minimal PyTorch Soft Actor Critic (SAC) implementation
Final project for big data and machine learning.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ 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. ๐๐๐
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 โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.