Published in

Inference in Graphical Models — Introduction to Variable Elimination

In a former article, we talked about inference on Graphical Models. We specifically considered the complexity of both exact and approximate inference. As it turned out, both situations gave us problems. Therefore, in this article, we will instead consider the concept of Variable Elimination. We will try to understand the basic idea behind it and then look at its algorithm.

Understanding Variable Elimination




Data Scientists must think like an artist when finding a solution when creating a piece of code. ⚪️ Artists enjoy working on interesting problems, even if there is no obvious answer ⚪️ 🔵 Follow to join our 18K+ Unique DAILY Readers 🟠

Recommended from Medium

Differential Equations 31: The Wronskian Method

An Introduction to the IS and LM Curves— Macro Economy

Discrete Math — The Basics of Lexical Analysis: DFA and NFA


Two Numbers Puzzle

Towards an intuitive understanding of quantum computing: Algorithms

Binary Search !!

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Helene Kegel

Helene Kegel

More from Medium

Bayesian Networks — Reasoning Patterns

How L1 regularization brings sparsity

Conditional Independence

Robust Statistics: The Maximum Bias Curve