Implementations from a graduate course following "Pattern Recognition and Machine Learning) written by Bishop and published in 2006.
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Updated
Sep 16, 2013 - MATLAB
Implementations from a graduate course following "Pattern Recognition and Machine Learning) written by Bishop and published in 2006.
Implementations of various online inference algorithms for LDA, with Python interface.
Variational Autoencoder with Recurrent Neural Network based on Google DeepMind's "DRAW: A Recurrent Neural Network For Image Generation"
Course/Homework materials for the "Creative Applications of Deep Learning with Tensorflow" MOOC
Repository to explore Generative Models
Tensorflow implementation of conditional variational auto-encoder for MNIST
Experiments of amortized stein variational gradient
Code for "Content-Based Social Recommendation with Poisson Matrix Factorization" (ECML-PKDD 2017)
Variational inference for covariate latent variable models
PixelVAE with or without regularization
Bayesian dessert for Lasagne
This is the code for our publication Inferring Latent States in a Network Influenced by Neighbor Activities: An Undirected Generative Approach, IEEE International Conference on Acoustics, Speech and Signal Processing, New Orleans, LA, 2017
Implementations of polygamma, lgamma, and beta functions for PyTorch
A toy model of Friston's active inference in Tensorflow
Variational Autoencoder in Pytorch
Implementation of Sequential Variational Autoencoder
Bayesian Linear regression using MCMC and Variational Inference
Variational Inference for Langevin Equations
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