Determine Function from Stationary Points
More resources available at www.misterwootube.com
From playlist Applications of Differentiation
Exploring Stationary Points (2 of 3: Introductory Examples regarding nature of Stationary Points)
More resources available at www.misterwootube.com
From playlist Applications of Differentiation
A Stationary Phase Method for a Class of Nonlinear Equations - Yen Do
Yen Do Georgia Institute of Technology October 26, 2010 In this talk I will describe a real-variable method to extract long-time asymptotics for solutions of many nonlinear equations (including the Schrodinger and mKdV equations). The method has many resemblances to the classical stationa
From playlist Mathematics
Understanding Stationary Points (3 of 3: Determining nature)
More resources available at www.misterwootube.com
From playlist Applications of Differentiation
Determining the nature of stationary points - Differentiation
Do some complex problems on differentiation finding stationary points and evaluating their nature by first derivative test.
From playlist Further Calculus - MAM Unit 3
Double Derivative Calculus Test - Nature of Stationary Points
In this video, we look at classifying the nature of stationary points using the double derivative calculus test. A stationary point occurs when the first derivative is equal to zero, but whether this stationary point is a local maximum, local minimum or a stationary point of inflection rem
From playlist Calculus
Exploring Stationary Points (1 of 3: In Depth Introduction to Stationary Points)
More resources available at www.misterwootube.com
From playlist Applications of Differentiation
Stochastic Homogenization (Lecture 2) 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)
Nature of some stationary varifolds near multiplicity 2 tangent planes - Neshan Wickramasekera
Workshop on Geometric Functionals: Analysis and Applications Topic: Nature of some stationary varifolds near multiplicity 2 tangent planes Speaker: Neshan Wickramasekera Affiliation: University of Cambridge; Member, School of Mathematics Date: March 6, 2019 For more video please visit ht
From playlist Mathematics
Reinhold Schneider - Multi-Reference Coupled Cluster for Computation of Excited States & Tensors
Recorded 29 March 2023. Reinhold Schneider of the Technische Universität Berlin presents "A Multi-Reference Coupled Cluster Method for the Computation of Excited States and Tensor Networks (QC-DMRG)" at IPAM's Increasing the Length, Time, and Accuracy of Materials Modeling Using Exascale C
From playlist 2023 Increasing the Length, Time, and Accuracy of Materials Modeling Using Exascale Computing
This lecture continues our discussion of the sphere, relating inversive geometry on the plane to the more fundamental inversive geometry of the sphere, introducing the Riemann sphere model of the complex plane with a point at infinity. Then we discuss the sphere as the projective line ove
From playlist Algebraic Topology: a beginner's course - N J Wildberger
36th Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series Talk
Title: Methods for $\ell_p$-$\ell_q$ minimization with applications to image restoration and regression with nonconvex loss and penalty. Date: December 1, 2021, 10:00am Eastern Time Zone (US & Canada) / 2:00pm GMT Speaker: Lothar Reichel, Kent State University Abstract: Minimization prob
From playlist Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series
Positive Lyapunov exponents and mixing in stochastic fluid flow. Part II - Elia Bruè
Topics in Analysis Topic: Positive Lyapunov exponents and mixing in stochastic fluid flow. Part II Speaker: Elia Bruè Affiliation: Member, School of Mathematics Date: April 28, 2022 In this three-part lecture series, we will present a series of works by Bedrossian, Blumenthal and Punsho
From playlist Mathematics
Stationary Points: Step-by-Step Guide
More resources available at www.misterwootube.com
From playlist Applications of Differentiation
Stanford Seminar - Towards theories of single-trial high dimensional neural data analysis
EE380: Computer Systems Colloquium Seminar Towards theories of single-trial high dimensional neural data analysis Speaker: Surya Ganguli, Stanford, Applied Physics Neuroscience has entered a golden age in which experimental technologies now allow us to record thousands of neurons, over
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series
Rolf Schneider: Hyperplane tessellations in Euclidean and spherical spaces
Abstract: Random mosaics generated by stationary Poisson hyperplane processes in Euclidean space are a much studied object of Stochastic Geometry, and their typical cells or zero cells belong to the most prominent models of random polytopes. After a brief review, we turn to analogues in sp
From playlist Probability and Statistics
(8.1.1) Systems of Autonomous Nonlinear Differential Equations and Phase Plane Analysis
This video defines autonomous systems of differential equations, how to analyze phase portraits and determine the equilibrium solutions. https://mathispower4u.com
From playlist Differential Equations: Complete Set of Course Videos
A full classification of finite adversarial partial monitoring - Tor Lattimore
The workshop aims at bringing together researchers working on the theoretical foundations of learning, with an emphasis on methods at the intersection of statistics, probability and optimization. Abstract: Partial monitoring is a generalisation of the multi-armed bandit framework that mod
From playlist The Interplay between Statistics and Optimization in Learning
Graphing Stationary Points (3 of 3: Visualising the second derivative)
More resources available at www.misterwootube.com
From playlist Applications of Differentiation
A Geometric View on Private Gradient-Based Optimization
A Google TechTalk, presented by Steven Wu, 2021/04/16 ABSTRACT: Differential Privacy for ML Series. Deep learning models are increasingly popular in many machine learning applications where the training data may contain sensitive information. To provide formal and rigorous privacy guaran
From playlist Differential Privacy for ML