Heiko Strathmann

Code for the paper "A Kernel Test of Goodness of Fit" by Kacper Chwialkowski, Heiko Strathmann, Arthur Gretton

Various estimators of the infinite dimensional exponential family model

Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"

Implementation of Russian Roulette for a GMRF on ozone data

Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"

Efficient and principled score estimation with Nyström kernel exponential families

Code for Kernel Adaptive Metropolis-Hastings

Public wiki of the Shogun Machine Learning Toolbox

Ready to use implementations of various Deep Learning algorithms using TensorFlow.

Material for the lab-session of the "Intro to ML" course at UCL.

No description provided.

Python framework for independent computation with backends for batch clusters

Random kitchen sink version of Kameleon MCMC

Minimal Java framework to implement and experiment with various two-player-game tree search algorithms

Writeup & code for Kamiltonian Monte Carlo Project

Linear algebra based on WG21

The Shogun Machine Learning Toolbox (Source Code)

NumFOCUS participation information for Google Season Of Docs

Arno

No description provided.

No description provided.

A framework for large-scale machine learning and graph computation.

PyStan: Python interface to Stan

PyMC version 3 (PyMC 2 is in branch 2.3)

Optimizing GPU-meta-programming code generating array oriented optimizing math compiler in Python

Notes for the theoretical Neuroscience course of the Gatsby Unit, UCL

Shogun Tutorial

The Shogun Machine Learning Toolbox (Data Sets)