Python implementation of Kernelized Locality Sensitive Hashing
BSD-3-CLAUSE License
Scikit-learn tutorials for the Scipy 2013 conference
Material for my lectures at the University of Oslo, Dec 2014
Material for my lectures at the ESAC statistics conference, Oct 27-31 2014
Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
Efficient pure Python implementation of Friedman's Supersmoother
Experimenting with pure-Python implementation of the NUFFT
A minimal Python kernel so you can run Python in your Python
k nearest neighbor (KNN) graphs via Pearson correlation distance and local sensitive hashing (LSH).
python tree algorithms for nearest neighbor search
My Talk for the 2014 OpenVisConf, April 24-25 in Boston, MA
SciPy 2013 Data Processing Tutorial
Work in progress for eventual contribution to scikit-learn
Code for the paper "A Kernel Test of Goodness of Fit" by Kacper Chwialkowski, Heiko Strathmann, A...
KD Trees for Sperical Data
Scikit-Learn Tutorial for PyData Seattle 2015