Mixture model

Mixture Models 4: multivariate Gaussians

Full lecture: http://bit.ly/EM-alg We generalise the equations for the case of a multivariate Gaussians. The main difference from the previous video (part 2) is that instead of a scalar variance we now estimate a covariance matrix, using the same posteriors as before.

From playlist Mixture Models

(ML 16.7) EM for the Gaussian mixture model (part 1)

Applying EM (Expectation-Maximization) to estimate the parameters of a Gaussian mixture model. Here we use the alternate formulation presented for (unconstrained) exponential families.

From playlist Machine Learning

(ML 16.6) Gaussian mixture model (Mixture of Gaussians)

Introduction to the mixture of Gaussians, a.k.a. Gaussian mixture model (GMM). This is often used for density estimation and clustering.

From playlist Machine Learning

Blender - New feature test: Smoke

For more information about the 3d software Blender please visit www.blender.org. www.kaikostack.com

From playlist Random Blender Tests

Automatic Pattern Matching for 3D Geometry in Blender

To help refining the alignment of multiple 3D scans with each other, I have written a new tool for Blender which automatically finds the best fit for mesh objects.

From playlist Random Blender Tests

(ML 16.8) EM for the Gaussian mixture model (part 2)

Applying EM (Expectation-Maximization) to estimate the parameters of a Gaussian mixture model. Here we use the alternate formulation presented for (unconstrained) exponential families.

From playlist Machine Learning

Mixture Models 3: multivariate Gaussians

Full lecture: http://bit.ly/EM-alg We generalise the equations for the case of a multivariate Gaussians. The main difference from the previous video (part 2) is that instead of a scalar variance we now estimate a covariance matrix, using the same posteriors as before.

From playlist Mixture Models

What is a solution? | Solutions | Chemistry | Don't Memorise

What is a solution? You would say it is a mixture of two or more liquids. But is it so? Are solutions just mixtures of liquids? Watch this video to know the answers to these questions. In this video, we will learn: 0:00 What is a mixture? 0:49 properties of mixtures 2:08 Types of mixtur

From playlist Chemistry

Mixture Models 5: how many Gaussians?

Full lecture: http://bit.ly/EM-alg How many components should we use in our mixture model? We can cross-validate to optimise the likelihood (or some other objective function). We can also use Occam's razor, formalised as the Bayes Information Criterion (BIC) or Akaike Information Criterio

From playlist Mixture Models

Robust and accurate inference via a mixture of Gaussian and terrors by Hyungsuk Tak

20 March 2017 to 25 March 2017 VENUE: Madhava Lecture Hall, ICTS, Bengaluru This joint program is co-sponsored by ICTS and SAMSI (as part of the SAMSI yearlong program on Astronomy; ASTRO). The primary goal of this program is to further enrich the international collaboration in the area

From playlist Time Series Analysis for Synoptic Surveys and Gravitational Wave Astronomy

Clustering (4): Gaussian Mixture Models and EM

Gaussian mixture models for clustering, including the Expectation Maximization (EM) algorithm for learning their parameters.

From playlist cs273a

Lecture 20 — Probabilistic Topic Models Mixture of Unigram Language Models | UIUC

From playlist Text Mining and Analytics [FULL COURSE] | UIUC

Clustering and Classification: Advanced Methods, Part 2

Data Science for Biologists Clustering and Classification: Advanced Methods Part 2 Course Website: data4bio.com Instructors: Nathan Kutz: faculty.washington.edu/kutz Bing Brunton: faculty.washington.edu/bbrunton Steve Brunton: faculty.washington.edu/sbrunton

From playlist Data Science for Biologists

Jason Morton: "An Algebraic Perspective on Deep Learning, Pt. 3"

Graduate Summer School 2012: Deep Learning, Feature Learning "An Algebraic Perspective on Deep Learning, Pt. 3" Jason Morton, Pennsylvania State University Institute for Pure and Applied Mathematics, UCLA July 20, 2012 For more information: https://www.ipam.ucla.edu/programs/summer-scho

From playlist GSS2012: Deep Learning, Feature Learning

Model-based clustering of high-dimensional data: Pitfalls & solutions - David Dunson

Virtual Workshop on Missing Data Challenges in Computation, Statistics and Applications Topic: Model-based clustering of high-dimensional data: Pitfalls & solutions Speaker: David Dunson Date: September 9, 2020 For more video please visit http://video.ias.edu

From playlist Mathematics

NIPS 2011 Music and Machine Learning Workshop: Automating Music Search and Recommendation

International Music and Machine Learning Workshop: Learning from Musical Structure at NIPS 2011 Invited Talk: Automating Music Search and Recommendation: an Active and Dynamic Learning Process by Gert Lanckriet Gert Lanckriet is an Associate Professor of the Department of Electrical

From playlist NIPS 2011 Music and Machine Learning Workshop

How To Create 3D Stylized Character Model In Blender | Session 03 | #gamedev

Don’t forget to subscribe! In this project series, you will learn to create 3D stylized character model in Blender. This project is about modeling/ sculpting a base mesh character that you can use in your own games. You will be learning all of the skills to be able to output high-quality

From playlist Create 3D Stylized Character Model In Blender

Alan Yuille: "Learning Discriminative Models of Objects and Images"

Graduate Summer School 2012: Deep Learning, Feature Learning "Learning Discriminative Models of Objects and Images" Alan Yuille, UCLA Institute for Pure and Applied Mathematics, UCLA July 13, 2012 For more information: https://www.ipam.ucla.edu/programs/summer-schools/graduate-summer-sc

From playlist GSS2012: Deep Learning, Feature Learning