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Infer.NET Team Blog
Infer.NET is a framework for running Bayesian inference in graphical models.
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Bayesian PCA
causal inference
causality
causation
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gates
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Blog Post:
Community-Based Bayesian Classifier Combination
Matteo Venanzi
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...
on
25 Jun 2014
Blog Post:
Causal inference with Infer.NET
John Winn
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...
on
27 Jan 2012
Blog Post:
Bayesian PCA
John Guiver
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...
on
30 Sep 2011
Blog Post:
Performance improvements in Infer.NET 2.4
John Guiver
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...
on
30 Sep 2011
Blog Post:
Calibrating reviews of conference submissions
John Guiver
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...
on
30 Sep 2011
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