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Peter Henderson's Projects

drqa icon drqa

A pytorch implementation of Reading Wikipedia to Answer Open-Domain Questions.

echo icon echo

Android Mesh Networking Chat with WiFI-Direct

echo-laptop icon echo-laptop

This is the laptop client to to connect to echo nodes

embeddedos icon embeddedos

A proof of concept sandbox for developing a Chaotically Randomized execution program on an Arduino Uno

endtoendpresentation icon endtoendpresentation

Presentation for reading group on Levine et al. End-to-end Learning of Visuomotor Policies

gym-extensions icon gym-extensions

This repo is intended as an extension for OpenAI Gym for auxiliary tasks (multitask learning, transfer learning, inverse reinforcement learning, etc.)

homebrew-breakend icon homebrew-breakend

Custom tap for Homebrew recipes that might be useful that aren't in the core.

hyde-hugo-starter icon hyde-hugo-starter

A starter using @SPF13's ported Hyde Theme for Hugo and Forestry as a Content Manager. Demo Site:

icarus icon icarus

A scalable simulator for evaluating the performance of in-network caches in Information Centric Networking (ICN)

jrae icon jrae

I re-implemented a semi-supervised recursive autoencoder in java. I think it is a pretty nice technique. Check it out! Or fork it

legalbench icon legalbench

An open science effort to benchmark legal reasoning in foundation models

libmei icon libmei

C++ library and Python bindings for the Music Encoding Initiative format

lnraw icon lnraw

Lab Notebook - Source Version

mcgill-codejam-2012 icon mcgill-codejam-2012

Team Gredona's submission for the 2012 McGill Codejam. Algorithmic trading platform for Morgan Stanley's Electronic Trading Group. Implemented in Java.

minidc icon minidc

A Java (and parts of a C++ in wrongly named java-impl branch) trial in TDD for making a mini version of the terminal dc calculator

motiondetection icon motiondetection

A project on motion detection in a noisy environment (shaky or moving camera), through background subtraction with single Gaussian models.

multistepbootstrappinginrl icon multistepbootstrappinginrl

Here, we compare Q(\sigma) learning presented by Sutton and Barto in [1] to Tree-Backup, n-step Expected Sarsa, and n-step Sarsa.

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