ClassroomThe classroom
Back to the lesson libraryMECHANISM · 11 MIN
M06.7 CONNECT THE MECHANISM

Learn distributions over plausible explanations

One café has two glowing reviews; another has 180 out of 200. Which should you trust? Learn to keep every plausible explanation in view instead of betting on one.

LESSON OVERVIEW11 min lesson

Lesson overview

One café has two glowing reviews; another has 180 out of 200. Which should you trust? Learn to keep every plausible explanation in view instead of betting on one.

What you’ll explore

  • Bayesian learning updates uncertain parameters or functions; Gaussian processes, variational approximations, and probabilistic programs offer different representations and computational tradeoffs.
GO TO THE SOURCE

Original explanations, connected to the research.

Deep Learning — probability and information theoryGaussian Processes for Machine Learning — authors’ bookVariational Inference: A Review for Statisticians (Blei, Kucukelbir, McAuliffe, 2017)
Suggest a correction

A precise note can make an explanation better.

Choose the scene and describe what needs attention. Download a feedback file to share through a channel you already use. This page does not send feedback or connect you with a reviewer.

The file includes this note, the scene title, and lesson metadata. Your saved progress and quiz responses are excluded. Download before leaving or reloading to keep your note.