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approxklvb

ars-reparameterization

Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)

autograd

Efficiently computes derivatives of numpy code.

clgp

Categorical Latent Gaussian Process

climin

Optimizers for machine learning

deep-exponential-families

Deep exponential families (DEFs)

deepgpy

Deep GPs with GPy

draw

Reimplementation of DRAW

dynamic-memory-networks-in-theano

Implementation of Dynamic memory networks by Kumar et al. http://arxiv.org/abs/1506.07285

dynamic_rnn_tensorflow

edward

A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.

elbow

Flexible Bayesian inference using TensorFlow

ep-stan

fastdual

gamma_sgvb

ggplot

ggplot for python

gpflow

gpstuff

GPstuff - Gaussian process models for Bayesian analysis

iaf

Code for reproducing key results in the paper "Improving Variational Inference with Inverse Autoregressive Flow"

ibayeslrule

Code for ICML 2020 paper on “Handling the Positive-Definite Constraint in the Bayesian Learning Rule”

improved-gan

code for the paper "Improved Techniques for Training GANs"

jax

GPU- and TPU-backed NumPy with differentiation and JIT compilation.

jsat

Java Statistical Analysis Tool, a Java library for Machine Learning

kfac-pytorch

Pytorch implementation of KFAC and E-KFAC (Natural Gradient).

klmethods

lightning

Large-scale linear classification, regression and ranking in Python

linregvb

Code for my paper "Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression"

models

Models built with TensorFlow

neural-tangents

Fast and Easy Infinite Neural Networks in Python

optim.jl

Optimization functions for Julia