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A Collection of Literature on Probabilistic Graphical Models

The collection of literature work on Probabilistic Graphical Models (PGMs). Source file can be found at git repository pgm-map.

Book and Monograph on PGMs

Books / Monograph:

Inference and Learning of PGMs Papers

Inference methods and techniques

Classical Inference Methods

Improvements

Application

Variational methods

Neural network based methods

Deep learning based methods

Learning messages

Graphical Neural Networks

Neural density function estimation

Learning of Graphical Models

Parameter Learning

Alternative objective

Learning graphical model parameters by approximate inference

Learning of MRF with neural networks

Learning of Directed Graphs

course materials on pgm

PGM, Logic & Decision-making in Dynamic Systems

Dynamics

Logic

  • ProbLog
    • D. Fierens, G. Van den Broeck, 2015. Inference and learning in probabilistic logic programs using weighted Boolean formulas.
    • L. De Raedt, A. Kimmig and H. Toivonen, 2017. ProbLog: A probabilistic Prolog and its application in link discovery.
  • Probabilistic Circuit

Decision-making

Courses

Platform

In Connecting with Others

Causality

Repos on Variational Inference

GANs

Optimal Transport (likelihood-free learning)