C17 Non homogeneous higher order linear ODEs with constant coefficients
Explanation of the methods involved in solving a non-homogeneous, linear, ODE, with constant coefficients.
From playlist Differential Equations
what is linear and non linear in machine learning, deep learning
what is linear and non linear in machine learning and deep learning? you will have clear understanding after watching this video. all machine learning youtube videos from me, https://www.youtube.com/playlist?list=PLVNY1HnUlO26x597OgAN8TCgGTiE-38D6
From playlist Machine Learning
Intro to Linear Systems: 2 Equations, 2 Unknowns - Dr Chris Tisdell Live Stream
Free ebook http://tinyurl.com/EngMathYT Basic introduction to linear systems. We discuss the case with 2 equations and 2 unknowns. A linear system is a mathematical model of a system based on the use of a linear operator. Linear systems typically exhibit features and properties that ar
From playlist Intro to Linear Systems
A14 Nonhomegeneous linear systems solved by undetermined coefficients
There are two methods for solving nonhomogeneous systems. The first uses undetermined coefficients.
From playlist A Second Course in Differential Equations
Review of Linear Time Invariant Systems
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Review: systems, linear systems, time invariant systems, impulse response and convolution, linear constant-coefficient difference equations
From playlist Introduction and Background
(8.1) A General Approach to Nonlinear Differential Questions
This video briefly describes the approach to gaining information about the solution to nonlinear differential equations. https://mathispower4u.com
From playlist Differential Equations: Complete Set of Course Videos
NLMEModeling: Nonlinear Mixed Effects Modeling of Dynamical Systems
Nonlinear mixed effects (NLME) modeling is a powerful tool to analyze time series data from several individual entities. In this talk, we will give a brief overview of a package for NLME modeling in Mathematica entitled NLMEModeling, implementing the so-called first-order conditional estim
From playlist Wolfram Technology Conference 2021
Marta D'Elia: A coupling strategy for nonlocal and local models with applications ...
The use of nonlocal models in science and engineering applications has been steadily increasing over the past decade. The ability of nonlocal theories to accurately capture effects that are difficult or impossible to represent by local Partial Differential Equation (PDE) models motivates a
From playlist HIM Lectures: Trimester Program "Multiscale Problems"
James Thorson - Forecasting non-local climate impacts for mobile marine species using extensions...
Dr James Thorson (National Oceanic and Atmospheric Administration) presents "Forecasting non-local climate impacts for mobile marine species using extensions to empirical orthogonal function analysis", 8 May 2020.
From playlist Statistics Across Campuses
Lisa Nickerson - Addressing Confounds in Neuroimaging Machine Learning Predictions - IPAM at UCLA
Recorded 13 January 2023. Lisa Nickerson of Harvard Medical School presents "Addressing Confounds in Neuroimaging Machine Learning Predictions" at IPAM's Explainable AI for the Sciences: Towards Novel Insights Workshop. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/expl
From playlist 2023 Explainable AI for the Sciences: Towards Novel Insights
DDPS | Towards Robust, Accurate & Tractable Reduced-Order Models
Talk Abstract This talk presents advances towards the development of effective projection-based reduced order models (ROMs) for complex multi-scale multi-physics problems. As a representative application, we consider combustion dynamics in a rocket engine, which is characterized by the c
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
Håvard Rue: Bayesian computation with INLA
Abstract: This talk focuses on the estimation of the distribution of unobserved nodes in large random graphs from the observation of very few edges. These graphs naturally model tournaments involving a large number of players (the nodes) where the ability to win of each player is unknown.
From playlist Probability and Statistics
DDPS | Physics-Informed Learning for Nonlinear Dynamical Systems
Talk Abstract Dynamical modeling of a process is essential to study its dynamical behavior and perform engineering studies such as control and optimization. With the ease of accessibility of data, learning models directly from the data have recently drawn much attention. It is also desir
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
14. Linear vs Nonlinear models
The simplest algorithms we can use for machine learning are linear models. In this video we talk about what makes a model linear and why this means more than just y=mx+b. We also explain nonlinear models with an example of materials data. We examine which is better by plotting residuals an
From playlist Materials Informatics
Noah Zaitlen: "A Short Tutorial on Linear Mixed Model Association Testing in Genetics"
Computational Genomics Winter Institute 2018 "A Short Tutorial on Linear Mixed Model Association Testing in Genetics" Noah Zaitlen, University of California, San Francisco Institute for Pure and Applied Mathematics, UCLA March 1, 2018 For more information: http://computationalgenomics.b
From playlist Computational Genomics Winter Institute 2018
The Effect of Stratification on Near-Inertial Waves Propagating on a Beta... by Siva Heramb Peddada
DISCUSSION MEETING WAVES, INSTABILITIES AND MIXING IN ROTATING AND STRATIFIED FLOWS (ONLINE) ORGANIZERS: Thierry Dauxois (CNRS & ENS de Lyon, France), Sylvain Joubaud (ENS de Lyon, France), Manikandan Mathur (IIT Madras, India), Philippe Odier (ENS de Lyon, France) and Anubhab Roy (IIT M
From playlist Waves, Instabilities and Mixing in Rotating and Stratified Flows (ONLINE)
Distinguished Visitor Lecture Series by Mark van der Laan Targeted Learning with Applications to ..
Distinguished Visitor Lecture Series Targeted Learning with Applications to Genomic Studies Mark van der Laan University of California, Berkeley, USA
From playlist Distinguished Visitors Lecture Series
B27 Introduction to linear models
Now that we finally now some techniques to solve simple differential equations, let's apply them to some real-world problems.
From playlist Differential Equations