ornithos/athenstimeseries2018

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Created over 6 years ago
Updated over 6 years ago

ornithos/athenstimeseries2018

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Time series excercises for the ACM data science summer school - Athens 2018

compare_df

Compare two dataframes

ProbLineSearch.jl

Probabilistic Line Searches for Stochastic Optimization (Mahsereci & Hennig, 2017) ported from MATLAB.

teachingnotes

Jupyter Notebook

SeqAdaptiveIS

Sequential adaptive importance sampling for static (and non-static) sequential problems.

pytorch-mtds-mocap

Implementation of Mocap application for MTDS

heroku-sqlgen

Heroku hosted SQL Generation for demo purposes

MTDS.jl

Implementation of some examples of multi-task dynamical system (in Julia).

Jupyter Notebook

matlabParser

A file to parse called and assigned variables in MATLAB

AxUtil.jl

A collection of utilities I've developed while working with Julia

dynamicalSystems

Collection of dynamical system implementations

mocap-mtds

Multi-Task Dynamical Systems for Mocap Data

Jupyter Notebook

pySQLGen

Generating SQL for OMOP standard relational databases via Python

pyalexutil

Various utilities for python.

matlab-utils

Assortment of MATLAB utility scripts

heroku-decovid-temp

InferGMM.jl

Implementation of GMM and various inference methods using GMMs

lpsvm

(UCL) Project work for large scale SVM solver

mtds-dblpend

MTDS applied to video data of a double pendulum

Jupyter Notebook

stan-intro

Initial exploration of stan, including user defined functions

AxPlot.jl

Plotting utilities for Julia (PyPlot) spun out from my utils package.

pynamicalsystem

a library of (discrete time) dynamical system code written in python. In part a port of the dynamicalSystems MATLAB repo.

nectr

nectr: Non-parametric Exploratory Clustering with TURN-RES. This is an R package including an implementation of the non-parametric clustering method authored by Foss, 2002. It was designed for industry analysts who need a fast way to explore a low dimension (p<10) dataset which does not impose a priori assumptions on the structure of the data.