Infer.NET Team Blog

Infer.NET is a framework for running Bayesian inference in graphical models.

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  • Blog Post: Community-Based Bayesian Classifier Combination

    In this post, we're going to discuss how to use Infer.NET to implement the Community-based Bayesian Classifier Combination (ComminityBCC) model for aggregating crowd-sourced labels described in the paper: Matteo Venanzi, John Guiver, Gabriella Kazai, Pushmeet Kohli, and Milad Shokouhi, Community...
  • Blog Post: Causal inference with Infer.NET

    Update: The paper Causality with Gates is now available which describes the theory behind this blog post. An oft quoted phrase is "correlation does not imply causation". It means that if A tends to be true when B is true (i.e. A and B are correlated), then it is not correct to assume that A causes...
  • Blog Post: Bayesian PCA

    This blog has been migrated from community.research.microsoft.com Original date of blog: February 3, 2009 Original blog author: John Guiver NOTE: This example and the corresponding code are now directly available in the Infer.NET release. It’s been a couple of months now since we’ve...
  • Blog Post: Performance improvements in Infer.NET 2.4

    This blog has been migrated from community.research.microsoft.com Original date of blog: November 8, 2010 Original blog author: John Winn Hello Infernauts!! Now that version 2.4 of Infer.NET is released, we're planning a series of blog posts to describe the new features and capabilities that...
  • Blog Post: Calibrating reviews of conference submissions

    This post has been migrated from community.research.microsoft.com. Original date of blog: February 1, 2010 Original blog author: John Guiver In this post, we're going to look at how to use Infer.NET to streamline the conference reviewing process. The process in a typical computer science conference...
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