Here I’ll walk through a cool algorithm that adaptively approximates the column space of a matrix using random projections.
This post covers normalizing flows, and the RealNVP invertible neural network. It’s only 150 lines of code total!
This short post will cover graphical intuition and PyTorch code for two different kinds of whitening: batch and instance.
A tutorial for an algorithm I implemented in our plenoptic PyTorch package package to synthesize eigendistortions.
A Python implementation of the elegant algorithm introduced by Iain Murray et al. (2010).
What’s the best way to quantify and visualize distance between two positive definite matrices? Julia code included.
PyTorch implementation and explanation of SGD MCMC sampling w/ Langevin or Hamiltonian dynamics.