In network science, a critical point is a value of , which separates random networks that have a giant component from those that do not (i.e. it separates a network in a subcritical regime from one in a supercritical regime). Considering a random network with an average degree the critical point is where the average degree is defined by the fraction of the number of edges and nodes in the network, that is . (Wikipedia).
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From playlist Calculus
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From playlist Calculus
From playlist Applications of Calculus
Finding critical points of functions
Download the free PDF http://tinyurl.com/EngMathYT This is an example illustrating how to find and classify the critical points of functions of two variables. Such ideas rely on the second derivative test and are seen in university mathematics.
From playlist Several Variable Calculus / Vector Calculus
How to find + classify critical points of functions
Download the free PDF http://tinyurl.com/EngMathYT This video shows how to calculate and classify the critical points of functions of two variables. The ideas involve first and second order derivatives and are seen in university mathematics.
From playlist Several Variable Calculus / Vector Calculus
How to find critical points of functions
Download the free PDF from http://tinyurl.com/EngMathYT This is an example illustrating how to find and classify the critical points of functions of two variables. Such ideas rely on the second derivative test and are seen in university mathematics.
From playlist Mathematics for Finance & Actuarial Studies 2
Definition of critical numbers and two examples of how to find critical numbers for a polynomial and a rational function.
From playlist Calculus
How to find and classify critical points of functions
Download the free PDF from http://tinyurl.com/EngMathYT This video shows how to calculate and classify the critical points of functions of two variables. The ideas involve first and second order derivatives and are seen in university mathematics.
From playlist Mathematics for Finance & Actuarial Studies 2
@Coin_Artist interviews Andreas Antonopoulos and David Irvine
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From playlist Interviews and Shows
SICSS 2017 - Guest Lecture by Sandra Gonzalez-Bailon (Day 4. June 22, 2017)
The first Summer Institute in Computational Social Science was held at Princeton University from June 18 to July 1, 2017, sponsored by the Russell Sage Foundation. For more details, please visit https://compsocialscience.github.io/summer-institute/2017/
From playlist Guest Speakers
Shi-Ju Ran: "Deep learning quantum states for Hamiltonian predictions"
Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021 Workshop II: Tensor Network States and Applications "Deep learning quantum states for Hamiltonian predictions" Shi-Ju Ran - Capital Normal University Abstract: Human experts cannot efficiently access the phys
From playlist Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021
An Introduction to Tensor Renormalization Group by Daisuke Kadoh
PROGRAM NONPERTURBATIVE AND NUMERICAL APPROACHES TO QUANTUM GRAVITY, STRING THEORY AND HOLOGRAPHY (HYBRID) ORGANIZERS: David Berenstein (University of California, Santa Barbara, USA), Simon Catterall (Syracuse University, USA), Masanori Hanada (University of Surrey, UK), Anosh Joseph (II
From playlist NUMSTRING 2022
Alessandra Bernardi: "On the Dimension of Tensor Network Varieties"
Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021 Workshop IV: Efficient Tensor Representations for Learning and Computational Complexity "On the Dimension of Tensor Network Varieties" Alessandra Bernardi - Università di Trento Abstract: I discuss the proble
From playlist Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021
Where does the statistics of complex systems come from? by Stefan Thurner
Program Summer Research Program on Dynamics of Complex Systems ORGANIZERS: Amit Apte, Soumitro Banerjee, Pranay Goel, Partha Guha, Neelima Gupte, Govindan Rangarajan and Somdatta Sinha DATE : 15 May 2019 to 12 July 2019 VENUE : Madhava hall for Summer School & Ramanujan hall f
From playlist Summer Research Program On Dynamics Of Complex Systems 2019
Rémi Monasson: "Capacity-resolution trade-off in the optimal learning of multiple low-dimensiona..."
Machine Learning for Physics and the Physics of Learning 2019 Workshop IV: Using Physical Insights for Machine Learning "Capacity-resolution trade-off in the optimal learning of multiple low-dimensional manifolds by attractor neural networks" Rémi Monasson - Centre National de la Recher
From playlist Machine Learning for Physics and the Physics of Learning 2019
Automating Machine Learning | Data Science Institute
ABOUT THE TALK: Recent years have seen a widespread adoption of machine learning in industry and academia, impacting diverse areas from advertisement to personal medicine. As more and more areas adopt machine learning and data science techniques, the question arises on how much expertise
From playlist talks
(8.2.1) Isolated Critical Points and Almost Linear Systems of Nonlinear Systems of ODEs
This video explains how to determine if critical points of a nonlinear autonomous system of differential equations isolated and if the system is almost linear. https://mathispower4u.com
From playlist Differential Equations: Complete Set of Course Videos
CCoE Webinar Series: Inaugural Security Program at Internet2
Originally recorded July 24th, 2017 The presentation will cover the introduction of a security program to protect the national R&E network operated by Internet2. Discussed will the methodology to conduct a security risk assessment of the network, the findings from the assessment, and spec
From playlist Center for Applied Cybersecurity Research (CACR)
DSC - Geoffrey Fox gives the talk "Overview on Futuregrid"
Geoffrey Fox gives an Overview of FutureGrid at the Big Data for Science workshop held at the Pervasive Technology Institute, Indiana University. This event was put on by PTI's Digital Science Center July 26th - July 30th, 2010. Please view the Tutorial on Using FutureGrid with Craig St
From playlist Digital Science Center (DSC)
Stability of Critical Points (Differential Equations 37)
Using Critical Points to determine increasing and decreasing of general solutions to differential equations.
From playlist Differential Equations