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bayesian_probit

Implementation of a Metropolis Hasting and a Gibbs Sampler with auxiliary variables to sample from the posterior distribution of the coefficients of a probit model

binarynnwithsa

Using Simulated Annealing to train feedforward Binary Neural Networks with weights and activations constrained to {-1,1}

bnnmultiverse

Bayesian model selection for neural networks

cs274e

Project for CS274E - Deep Generative Models

giosueio.github.io_

hierarchicaldp

Simulating draws from a Hierarchical Dirichlet Process

laplace

Laplace approximations for Deep Learning.

tgs

R code to implement the (weighted) Tempered Gibbs Sampling algorithm

uci_grad_housing_choice

pick the optimal combination of apartments to save and maximize the probability of getting where you want.

wassersteinvi

Unofficial implementation of the paper Wasserstein Variational Inference by Ambrogioni et al. (2018).