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21 search results found

Deep Learning Drizzle ⭐ 10,767

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

Pomegranate ⭐ 3,194

Fast, flexible and easy to use probabilistic modelling in Python.

Turing.jl ⭐ 1,925

Bayesian inference with probabilistic programming.

Variational Autoencoder ⭐ 1,114

Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)

Variational Autoencoder ⭐ 1,049

Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)

Mbmlbook ⭐ 183

Sample code for the Model-Based Machine Learning book.

The Books Making You Better ⭐ 169

A list of time-lasting classic books, which not only help you figure out how it works, but also grasp when it works and why it works in that way.

Forneylab.jl ⭐ 134

Julia package for automatically generating Bayesian inference algorithms through message passing on Forney-style factor graphs.

scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics

Official Repository of "Contextual Graph Markov Model" (ICML 2018 - JMLR 2020)

Easy Factor Graph ⭐ 24

General purpose C++ library for managing discrete factor graphs

Blangsdk ⭐ 22

Blang's software development kit

Statistical Machine Learning ⭐ 16

Probabilistic Machine Learning course lab @UNITS

Orgainzed Digital Intelligent Network (O.D.I.N)

Machine Learning Summer Schools ⭐ 14

Curated materials for different machine learning related summer schools

A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions

Upgrad_pgdmlai ⭐ 11

assignments and group case studies from PGDMLAI course by upGrad & IIITB

Awesome Bayes Nets ⭐ 9

⚗️ A curated list of Books, Research Papers, and Software for Bayesian Networks.

An(other) implementation of Explicit Duration Hidden Semi-Markov Models in Python 3

Conditional Random Fields ⭐ 7

An analysis and implementation of Conditional Random Fields.

Integrated computational framework for reconstruction and parametrization of electronic band sturcture from photoemission spectroscopy data

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