Social network analysis | Algebraic graph theory
In graph theory and social network analysis, alpha centrality is an alternative name for Katz centrality. It is a measure of centrality of nodes within a graph. It is an adaptation of eigenvector centrality with the addition that nodes are imbued with importance from external sources. (Wikipedia).
Centrality - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Types Of Centrality - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Degree Centrality Solution - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Centralizer of a set in a group
A centralizer consider a subset of the set that constitutes a group and included all the elements in the group that commute with the elements in the subset. That's a mouthful, but in reality, it is actually an easy concept. In this video I also prove that the centralizer of a set in a gr
From playlist Abstract algebra
Paolo Boldi - Axioms for centrality: rank monotonicity for PageRank
https://indico.math.cnrs.fr/event/3475/attachments/2180/2562/Boldi_GomaxSlides.pdf
From playlist Google matrix: fundamentals, applications and beyond
Centralizer of an element in the dihedral group of order 6
Before we go on to the stabilizer of a set in a group, I want to use the dihedral group of order 6, select one of its elements and then go through the whole group to show that there are element that commute with this chosen element. I will do this wil the help of Mathematica. A shoutout
From playlist Abstract algebra
Mean v median: Measures of Central Tendency
Intro to measures of central tendency
From playlist Unit 1: Descriptive Statistics
The central limit theorem allows us to do statistical analysis through hypothesis testing. In short, is states that if we compile many, many means from sample taken from the same population, that the distribution of those means will be normally distributed.
From playlist Learning medical statistics with python and Jupyter notebooks
What is General Relativity? Lesson 26: The central force problem in classical mechanics
What is General Relativity? Lesson 26: The central force problem in classical mechanics In this lesson we prepare ourselves for the study of the Schwarzschild geodesic analysis by doing a deep review of the Lagrangian formalism of classical mechanics with a particular focus on the central
From playlist What is General Relativity?
J. Aramayona - MCG and infinite MCG (Part 2)
The first part of the course will be devoted to some of the classical results about mapping class groups of finite-type surfaces. Topics may include: generation by twists, Nielsen-Thurston classification, abelianization, isomorphic rigidity, geometry of combinatorial models. In the second
From playlist Ecole d'été 2018 - Teichmüller dynamics, mapping class groups and applications
Introduction to SNA. Lecture 4. Node centrality and ranking on networks.
Node centrality metrics, degree centrality, closeness centrality, betweenness centrality, eigenvector centrality. Status and rank prestige, PageRank,Hubs and Authorities. Lecture slides: http://www.leonidzhukov.net/hse/2015/sna/lectures/lecture4.pdf
From playlist Introduction to SNA
Supersymmetry and Superspace, Part 1 - Jon Bagger
Supersymmetry and Superspace, Part 1 Jon Bagger Johns Hopkins University July 19, 2010
From playlist PiTP 2010
Supersymmetry and Superspace, Part 3 - Jon Bagger
Supersymmetry and Superspace, Part 3 Jon Bagger Johns Hopkins University July 21, 2010
From playlist PiTP 2010
Permutation Orbifolds of Vertex Operator Algebras
This is a recording of a talk I gave at the Illinois State University Algebra Seminar. Suggest a problem: https://forms.gle/ea7Pw7HcKePGB4my5 Please Subscribe: https://www.youtube.com/michaelpennmath?sub_confirmation=1 Merch: https://teespring.com/stores/michael-penn-math Personal Websi
From playlist Research Talks
Trigonometry X: the Law of Cotangents (and another lovely relation involving cotangents!)
Boy, oh boy this is a longish one. I prove the Law of Cotangents using the incenter of the triangle, after motivating the path with another way one might seek to prove the Law of Sines using the circumcenter of the triangle. After that, I demonstrate an equally lovely relationship betwee
From playlist Trigonometry
Center of quantum group - Arun Kannan
Quantum Groups Seminar Topic: Center of quantum group Speaker: Arun Kannan Affiliation: Massachusetts Institute of Technology Date: February 04, 2021 For more video please visit http://video.ias.edu
From playlist Quantum Groups Seminar
The Heisenberg Algebra part 1.
We begin to describe the Heisenberg vertex algebra, which is an algebraic model of one free boson. Please Subscribe: https://www.youtube.com/michaelpennmath?sub_confirmation=1 Merch: https://teespring.com/stores/michael-penn-math Personal Website: http://www.michael-penn.net Randolph Col
From playlist Vertex Operator Algebras
Rare events in fat-tailed systems by Eli Barkai
Large deviation theory in statistical physics: Recent advances and future challenges DATE: 14 August 2017 to 13 October 2017 VENUE: Madhava Lecture Hall, ICTS, Bengaluru Large deviation theory made its way into statistical physics as a mathematical framework for studying equilibrium syst
From playlist Large deviation theory in statistical physics: Recent advances and future challenges
Marcelo Pereyra: Bayesian inference and mathematical imaging - Lecture 4: mixture...
Bayesian inference and mathematical imaging - Part 4: mixture, random fields and hierarchical models Abstract: This course presents an overview of modern Bayesian strategies for solving imaging inverse problems. We will start by introducing the Bayesian statistical decision theory framewo
From playlist Probability and Statistics
Understanding the Central Limit Theorem
From playlist Unit 7 Probability C: Sampling Distributions & Simulation