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Caspar Addyman's Projects

alienrabble icon alienrabble

Automatically exported from code.google.com/p/alienrabble

babyjokes icon babyjokes

Machine learning analysis of video dataset of parents demonstrating simple jokes to babies.

babysleepbraziluk icon babysleepbraziluk

Sleep diary study of infants in Sao Paulo, Brazil and United Kingdom. This repository contains the raw data and an R analysis file and the journal manuscript.

contec-pulse-oximeter-in-matlab icon contec-pulse-oximeter-in-matlab

Matlab code to collect real time data from Contec Pulse Oximeters (Heart rate monitor). Please note, this is unsupported and unofficial code that I am sharing in case it is any use to anyone.

gamit icon gamit

Gaussian Activation Model of Interval Timing - A matlab implementation.

help-yourself icon help-yourself

All the words and pictures from Caspar's first novel. This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.

notebookdemos icon notebookdemos

Using Jupyter notebooks for reproducible scientific analysis.

policies icon policies

Goldsmiths InfantLab policies and operating procedures

respond icon respond

An automated measure of caregiver responsiveness.

socialtv icon socialtv

Data, code and preprints for preschool social laughter study

syncpy icon syncpy

SyncPy is a novel open-source analytic library for investigating synchrony in a fast and exhaustive way.

timeasmemory icon timeasmemory

Matlab implementation of Addyman et al. memory based model of interval timing

tracx-matlab icon tracx-matlab

Matlab files for French, Addyman & Mareschal (2011). A neural network model of sequence learning in adults and infants.

tracx-python icon tracx-python

Neural network model of sequence learning in adults and infants, French, Addyman & Mareschal (2011)

tracx-web icon tracx-web

An online javascript based version of the TRACX neural network simulator for sequence learning. A version can be found here

vasc icon vasc

Video Actor Synchrony and Causality - Jupyter notebooks using OpenPose and SciPy to convert and analyses sets of videos as time-series data

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