VI - 4 - ELBO - Evidence Lower BOund

The ELBO is the part of the KL divergence that actually depends on our surrogate distribution q. So in VI our objective is to maximize the ELBO instead of minimizing the KL.

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“VI in R” Course Outline:
Administration
* Administration
Intro
* Intuition – what is VI?
* Notebook – Intuition
* Origin, Outline, Context
KL Divergence
* KL Introduction
* KL – Extra Intuition
* Notebook – KL – Exercises
* Notebook – KL – Additional Topics
* KL vs. Other Metrics
VI vs. ML
* VI (using KL) vs. Maximum Likelihood
ELBO & “Mean Field”
* ELBO
* “Mean Field” Approximation
Coordinate Ascent VI (CAVI)
* Coordinate Ascent VI (CAVI)
* Functional Derivative & Euler-Lagrange Equation
* CAVI – Toy Example
* CAVI – Bayesian GMM Example
* Notebook – Normal-Gamma Conjugate Prior
* Notebook – Bayesian GMM – Unknown Precision
* Notebook – Image Denoising (Ising Model)
Exponential Family
* CAVI for the Exponential Family
* Conjugacy in the Exponential Family
* Notebook – Latent Dirichlet Allocations Example
VI vs. EM
* VI vs. EM
Stochastic VI / Advanced VI
* SVI – Review
* SVI for Exponential Family
* Automatic Differentiation VI (ADVI)
* Notebook – ADVI Example (using STAN)
* Black Box VI (BBVI)
* Notebook – BBVI Example
Expectation Propagation
* Forward vs. Reverse KL
* Expectation Propagation

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Intro/Outro Music: Dreamer - by Johny Grimes

[MeerkatStatistics]

Full course is now available on my private website. Become a member and get full access:
* 🎉 Special YouTube 60% Discount on Yearly Plan – valid for the 1st 100 subscribers; Voucher code: First100 🎉 *

“VI in R” Course Outline:
Administration
* Administration
Intro
* Intuition – what is VI?
* Notebook – Intuition
* Origin, Outline, Context
KL Divergence
* KL Introduction
* KL – Extra Intuition
* Notebook – KL – Exercises
* Notebook – KL – Additional Topics
* KL vs. Other Metrics
VI vs. ML
* VI (using KL) vs. Maximum Likelihood
ELBO & “Mean Field”
* ELBO
* “Mean Field” Approximation
Coordinate Ascent VI (CAVI)
* Coordinate Ascent VI (CAVI)
* Functional Derivative & Euler-Lagrange Equation
* CAVI – Toy Example
* CAVI – Bayesian GMM Example
* Notebook – Normal-Gamma Conjugate Prior
* Notebook – Bayesian GMM – Unknown Precision
* Notebook – Image Denoising (Ising Model)
Exponential Family
* CAVI for the Exponential Family
* Conjugacy in the Exponential Family
* Notebook – Latent Dirichlet Allocations Example
VI vs. EM
* VI vs. EM
Stochastic VI / Advanced VI
* SVI – Review
* SVI for Exponential Family
* Automatic Differentiation VI (ADVI)
* Notebook – ADVI Example (using STAN)
* Black Box VI (BBVI)
* Notebook – BBVI Example
Expectation Propagation
* Forward vs. Reverse KL
* Expectation Propagation


Why become a member?
* All video content
* Extra material (notebooks)
* Access to code and notes
* Community Discussion
* No Ads
* Support the Creator ❤

[navintiwari]

Ah! Finally a good and to the point explanation after searching so much on YouTube. Thankyou! You have a new subscriber now.

[frederictost]

Sound is too low. Not very well explained.