Basic stochastic simulation b: Stochastic simulation algorithm
(C) 2012-2013 David Liao (lookatphysics.com) CC-BY-SA Specify system Determine duration until next event Exponentially distributed waiting times Determine what kind of reaction next event will be For more information, please search the internet for "stochastic simulation algorithm" or "kin
From playlist Probability, statistics, and stochastic processes
Discrete-Time Dynamical Systems
This video shows how discrete-time dynamical systems may be induced from continuous-time systems. https://www.eigensteve.com/
From playlist Data-Driven Dynamical Systems
From playlist Contributed talks One World Symposium 2020
Jana Cslovjecsek: Efficient algorithms for multistage stochastic integer programming using proximity
We consider the problem of solving integer programs of the form min {c^T x : Ax = b; x geq 0}, where A is a multistage stochastic matrix. We give an algorithm that solves this problem in fixed-parameter time f(d; ||A||_infty) n log^O(2d) n, where f is a computable function, d is the treed
From playlist Workshop: Parametrized complexity and discrete optimization
Closed loop discrete controller Lecture 2019-04-08
Evaluating the response of a continuous system controlled by a discrete controller using several methods
From playlist Discrete
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
Random Processes and Stationarity
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Introduction to describing random processes using first and second moments (mean and autocorrelation/autocovariance). Definition of a stationa
From playlist Random Signal Characterization
(ML 19.2) Existence of Gaussian processes
Statement of the theorem on existence of Gaussian processes, and an explanation of what it is saying.
From playlist Machine Learning
Markov processes and applications-3 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
Paolo Guasoni, Lesson I - 18 december 2017
QUANTITATIVE FINANCE SEMINARS @ SNS PROF. PAOLO GUASONI TOPICS IN PORTFOLIO CHOICE
From playlist Quantitative Finance Seminar @ SNS
Stilian Stoev: Function valued random fields: tangents, intrinsic stationarity, self-similarity
We study random fields taking values in a separable Hilbert space H. First, we focus on their local structure and establish a counterpart to Falconer's characterization of tangent fields. That is, we show (under general conditions) that the tangent fields to a H-valued process are self-sim
From playlist Probability and Statistics
Introduction to Linear Time Invariant System Descriptions
http://AllSignalProcessing.com for free e-book on frequency relationships and more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Introduces systems and their use in signal processing; defines linearity, time invariance, and causal sys
From playlist Introduction and Background
2 Ruediger - Stochastic Integration & SDEs
PROGRAM NAME :WINTER SCHOOL ON STOCHASTIC ANALYSIS AND CONTROL OF FLUID FLOW DATES Monday 03 Dec, 2012 - Thursday 20 Dec, 2012 VENUE School of Mathematics, Indian Institute of Science Education and Research, Thiruvananthapuram Stochastic analysis and control of fluid flow problems have
From playlist Winter School on Stochastic Analysis and Control of Fluid Flow
Martin Schweizer: Some stochastic Fubini theorems
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 Analysis and its Applications
Integrating Inference with Stochastic Process Algebra Models - Jane Hillston, Edinburgh
ProPPA is a probabilistic programming language for continuous-time dynamical systems, developed as an extension of the stochastic process algebra Bio-PEPA. It offers a high-level syntax for describing systems of interacting components with stochastic behaviours where some of the parameters
From playlist Logic and learning workshop
FinMath L2-2: The general Ito integral 2
Welcome to the second part of lesson 2. In this video we discuss some properties of the (general) Ito integral and introduce the necessary notions to deal with the Ito-Doeblin formula, which will be treated in Lesson 3. Topics: 00:00 A little exercise for you 06:46 Definition of the integ
From playlist Financial Mathematics
Markov processes and applications 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
Sebastian Ertel - An Ensemble Kalman-Bucy filter for correlated observation noise
Sebastian Ertel (Technical University of Berlin) presents, "An Ensemble Kalman-Bucy filter for correlated observation noise", 8/7/22.
From playlist Statistics Across Campuses
Some solvable Stochastic Control Problems
At the 2013 SIAM Annual Meeting, Tyrone Duncan of the University of Kansas described stochastic control problems for continuous time systems where optimal controls and optimal costs can be explicitly determined by a direct method. The applicability of this method is demonstrated by example
From playlist Complete lectures and talks: slides and audio
Introduction to Discrete and Continuous Variables
This video defines and provides examples of discrete and continuous variables.
From playlist Introduction to Functions: Function Basics