andymiller Goto Github PK

autograd

Efficiently computes derivatives of numpy code.

celestepy

Probabilistic modeling and bayesian inference of astronomical sources

cvg_scripts

dots

My dotfiles

dr-vae

pytorch code for discriminatively regularized variational autoencoders

ekg-risk-models

Code for for fitting EKG-based risk predictors.

featurebasedalignment

Registration for point clouds

flecks

nonparametric modeling of point processes

gpy

Gaussian processes framework in python

normflows

Simple normalizing flows example using autograd

pybasicbayes

pydtw

A python/numpy/cython implementation of dynamic time warping (DTW) for aligning time series.

pynic

Nonparametric Information Theoretic Clustering

pyro-mini-tutorial

reducedvariancereparamgradients

Reducing Reparameterization Gradient Variance code.

stampbuilder

Builds small image patches of SDSS data. Organizes corresponding spectra.

svae

code for Structured Variational Autoencoders

theanograd

Hooking theano gradients into autograd

vae-flow

Amortized variational inference with tensorflow.

vboost

code supplement for variational boosting (https://arxiv.org/abs/1611.06585)