Bayesian-thinking's repositories
Simple-Variational-Autoencoder
A VAE written entirely in Numpy/Cupy
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
tf-dagmm
Tensorflow Implementation of dagmm: Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection, Zong et al, 2018
ctv-TimeSeries
git mirror of CRAN Task View Time Series files
dagmm-1
My attempt at reproducing the paper Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection
data-science-your-way
Ways of doing Data Science Engineering and Machine Learning in R and Python
adversarial_gmm
Prototype code for paper: Adversarial Generalized Method of Moments, Greg Lewis and Vasilis Syrgkanis
Good-Papers
I try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my notes on some good papers
dagmm
A Pytorch implementation of the paper `Deep Autoencoding Gaussian Mixture Model For Unsupervised Anomaly Detection` by Zong et al.
BayesianLearning
Bayesian Machine Learning
bayes-nn
Lecture notes on Bayesian deep learning
Teaching-Stan-Hierarchical-Modelling
Jupyter notebooks for teaching hierarchical Bayesian modelling with Stan
autoencoder_explained
This is the code for "Autoencoder Explained" by Siraj Raval on Youtube
bayesian-belief-networks
Pythonic Bayesian Belief Network Package, supporting creation of and exact inference on Bayesian Belief Networks specified as pure python functions.
gsoc17-hhmm
Bayesian Hierarchical Hidden Markov Models applied to financial time series, a research replication project for Google Summer of Code 2017.
GMVAE
Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders
k_means_clustering
This is the code for "K-Means Clustering - The Math of Intelligence (Week 3)" By SIraj Raval on Youtube
Autoencoders
Torch implementations of various types of autoencoders
Gaussian_Mixture_Models
This is the code for "Gaussian Mixture Models - The Math of Intelligence (Week 7)" By Siraj Raval on Youtube
PersonalizedMultitaskLearning
Code for performing 3 multitask machine learning methods: deep neural networks, Multitask Multi-kernel Learning (MTMKL), and a hierarchical Bayesian model (HBLR).
awesome-bayesian-deep-learning
A curated list of resources dedicated to bayesian deep learning
Bayesian-Modelling-in-Python
A python tutorial on bayesian modeling techniques (PyMC3)
notes-on-dirichlet-processes
:game_die: IPython notebooks explaining Dirichlet Processes, HDPs, and Latent Dirichlet Allocation
VAE-Torch
Implementation of Variational Auto-Encoder in Torch7
DPMM
Dirichlet Process Mixture Models
em-gaussian
Python code for Expectation-Maximization estimate of Gaussian mixture model
cvae
Conditional variational autoencoder implementation in Torch