From playlist Contributed talks One World Symposium 2020
By popular request, this is a version of the video https://youtu.be/HfCQdFpNeLQ showing a linear wave hitting obstacles distributed according to a Poisson point process, but with a color scheme showing only the wave height. A Poisson point process is the most random distribution of points
From playlist Mangroves vs tsunamis (sort of)
Ofer Zeitouni: Freezing and decorated Poisson point processes
Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b
From playlist Probability and Statistics
Cluster size distribution for Bernoulli site percolation on a Poisson disc process
Like the recent video https://youtu.be/zvKh0rxQgAs , this simulation shows percolation on a Poisson disc process, but this time all clusters are shown in colors depending on their size. The Poisson disc process is similar to a Poisson point process (points thrown independently and uniforml
From playlist Percolation
MIT RES.6-012 Introduction to Probability, Spring 2018 View the complete course: https://ocw.mit.edu/RES-6-012S18 Instructor: John Tsitsiklis License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu
From playlist MIT RES.6-012 Introduction to Probability, Spring 2018
Comparing the Solutions to Homogeneous and Nonhomogeneous Systems
This video compares the solutions to a homogeneous system and nonhomogeneous system of equations.
From playlist Rank and Homogeneous Systems
Adrian Baddeley: The Poisson-saddlepoint approximation
Gibbs spatial point processes are important models in theoretical physics and in spatial statistics. After a brief survey of Gibbs point processes, we will present a method for approximating their most important characteristic, the intensity of the process. The method has some affinity wit
From playlist Probability and Statistics
Determine if a First-Order Differential Equation is Homogeneous - Part 1
This video explains how to determine if a given linear first order differential equation is homogeneous using the ratio definition. Website: http://mathispower4u.com
From playlist First Order Homogeneous Differential Equations
Poisson's Equation for Beginners: LET THERE BE GRAVITY and How It's Used in Physics | Parth G
The first 1000 people to use the link will get a free trial of Skillshare Premium Membership: https://skl.sh/parthg03211 The Poisson equation has many uses in physics... so we'll be understanding the basics of the mathematics behind it, and then applying it to the study of classical grav
From playlist Classical Physics by Parth G
Spatial Events: Spatial Statistics
Spatial point patterns are collections of randomly positioned events in space. Examples include trees in a forest, positions of stars, earthquakes, crime locations, animal sightings, etc. Spatial point data analysis, as a statistical exploration of point patterns, aims to answer questions
From playlist Wolfram Technology Conference 2021
Stochastic Homogenization (Lecture 3) by Andrey Piatnitski
DISCUSSION MEETING Multi-Scale Analysis: Thematic Lectures and Meeting (MATHLEC-2021, ONLINE) ORGANIZERS: Patrizia Donato (University of Rouen Normandie, France), Antonio Gaudiello (Università degli Studi di Napoli Federico II, Italy), Editha Jose (University of the Philippines Los Baño
From playlist Multi-scale Analysis: Thematic Lectures And Meeting (MATHLEC-2021) (ONLINE)
Connecting Random Connection Models by Srikanth K Iyer
PROGRAM: ADVANCES IN APPLIED PROBABILITY ORGANIZERS: Vivek Borkar, Sandeep Juneja, Kavita Ramanan, Devavrat Shah, and Piyush Srivastava DATE & TIME: 05 August 2019 to 17 August 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalore Applied probability has seen a revolutionary growth in resear
From playlist Advances in Applied Probability 2019
Spatial Events-Spatial Statistics
Spatial point patterns are collections of randomly positioned events in space. Examples include trees in a forest, positions of stars, earthquakes, crime locations, animal sightings, etc. Spatial point data analysis, as a statistical exploration of point patterns, aims to answer questions
From playlist Wolfram Technology Conference 2022
5. Poisson Combining and Splitting
MIT 6.262 Discrete Stochastic Processes, Spring 2011 View the complete course: http://ocw.mit.edu/6-262S11 Instructor: Robert Gallager License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.262 Discrete Stochastic Processes, Spring 2011
Wilhem Stannat - Fluctuation limits for mean-field interacting nonlinear Hawkes processes
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From playlist Workshop "Workshop on Mathematical Modeling and Statistical Analysis in Neuroscience" - January 31st - February 4th, 2022
Markov processes and applications-2 by Hugo Touchette
PROGRAM : BANGALORE SCHOOL ON STATISTICAL PHYSICS - XII (ONLINE) ORGANIZERS : Abhishek Dhar (ICTS-TIFR, Bengaluru) and Sanjib Sabhapandit (RRI, Bengaluru) DATE : 28 June 2021 to 09 July 2021 VENUE : Online Due to the ongoing COVID-19 pandemic, the school will be conducted through online
From playlist Bangalore School on Statistical Physics - XII (ONLINE) 2021
A Feynman Approach to Dynamic Rate Markov Processes - William A. Massey
Members’ Seminar Topic: A Feynman Approach to Dynamic Rate Markov Processes Speaker: William A. Massey Affiliation: Princeton University; Member, School of Mathematics Date: December 14, 2020 For more video please visit http://video.ias.edu
From playlist Mathematics
The Poisson boundary: a qualitative theory by Vadim Kaimanovich
Program Probabilistic Methods in Negative Curvature ORGANIZERS: Riddhipratim Basu, Anish Ghosh and Mahan Mj DATE: 11 March 2019 to 22 March 2019 VENUE: Madhava Lecture Hall, ICTS, Bangalore The focal area of the program lies at the juncture of three areas: Probability theory o
From playlist Probabilistic Methods in Negative Curvature - 2019
L22.2 Definition of the Poisson Process
MIT RES.6-012 Introduction to Probability, Spring 2018 View the complete course: https://ocw.mit.edu/RES-6-012S18 Instructor: John Tsitsiklis License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu
From playlist MIT RES.6-012 Introduction to Probability, Spring 2018