Fractal analysis is useful in the study of complex networks, present in both natural and artificial systems such as computer systems, brain and social networks, allowing further development of the field in network science. (Wikipedia).
Dimensions (1 of 3: The Traditional Definition - Directions)
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From playlist Exploring Mathematics: Fractals
Fractals are typically not self-similar
An explanation of fractal dimension. Help fund future projects: https://www.patreon.com/3blue1brown An equally valuable form of support is to simply share some of the videos. Special thanks to these supporters: https://3b1b.co/fractals-thanks And by Affirm: https://www.affirm.com/careers H
From playlist Explainers
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From playlist research
Dimensions (2 of 3: A More Flexible Definition - Scale Factor)
More resources available at www.misterwootube.com
From playlist Exploring Mathematics: Fractals
In this video, I define a neat concept called the fractal derivative (which shouldn't be confused with fractional derivatives). Then I provide a couple of examples, and finally I present an application of this concept to the study of anomalous diffusion in physics. Enjoy!
From playlist Calculus
Dimensions (3 of 3: Fractal Dimensions)
More resources available at www.misterwootube.com
From playlist Exploring Mathematics: Fractals
Summer of math exposition submission- fractal calculus
Fractal Calculus
From playlist Summer of Math Exposition Youtube Videos
David Aasen - Topological Defect Networks for Fracton Models - IPAM at UCLA
Recorded 30 August 2021. David Aasen of Microsoft Station Q presents "Topological Defect Networks for Fracton Models" at IPAM's Graduate Summer School: Mathematics of Topological Phases of Matter. Learn more online at: http://www.ipam.ucla.edu/programs/summer-schools/graduate-summer-school
From playlist Graduate Summer School 2021: Mathematics of Topological Phases of Matter
Ginestra Bianconi (8/28/21): The topological Dirac operator and the dynamics of topological signals
Topological signals associated not only to nodes but also to links and to the higher dimensional simplices of simplicial complexes are attracting increasing interest in signal processing, machine learning and network science. Typically, topological signals of a given dimension are investig
From playlist Beyond TDA - Persistent functions and its applications in data sciences, 2021
Tipping in Thermoacoustic Systems and Their Early Warning Signals by R. I. Sujith
PROGRAM TIPPING POINTS IN COMPLEX SYSTEMS (HYBRID) ORGANIZERS: Partha Sharathi Dutta (IIT Ropar, India), Vishwesha Guttal (IISc, India), Mohit Kumar Jolly (IISc, India) and Sudipta Kumar Sinha (IIT Ropar, India) DATE: 19 September 2022 to 30 September 2022 VENUE: Ramanujan Lecture Hall an
From playlist TIPPING POINTS IN COMPLEX SYSTEMS (HYBRID, 2022)
A TQFT Perspective on Fracton Order
IAS High Energy Theory Seminar Topic: A TQFT Perspective on Fracton Order Speaker: Abhinav Prem Affiliation: Institute for Advanced Study Date: September 23, 2022 Fracton phases of matter exhibit striking behaviour which seemingly renders them beyond the standard topological quantum fiel
From playlist IAS High Energy Theory Seminar
Decimated Navier-Stokes turbulence by Samriddhi Sankar Ray
PROGRAM DYNAMICS OF COMPLEX SYSTEMS 2018 ORGANIZERS Amit Apte, Soumitro Banerjee, Pranay Goel, Partha Guha, Neelima Gupte, Govindan Rangarajan and Somdatta Sinha DATE: 16 June 2018 to 30 June 2018 VENUE: Ramanujan hall for Summer School held from 16 - 25 June, 2018; Madhava hall for W
From playlist Dynamics of Complex systems 2018
Delicia Kamins - Philosophy of Fractals - CoM Oct 2020
We know that fractals are nature’s pattern makers. Fractals are in fact everywhere we look: tree bark, snowflakes, mountain ranges, cloud, rivers, seashells, all the way up to the shape of galaxies. Beyond nature, however, human beings are fractal thinkers. We depend on fractal algorithms
From playlist Celebration of Mind
Festive Fractals - Computerphile
Fractals aren't just fascinating computer generated patterns, they could also be the key to future computer architecture. Professor Phil Moriarty explains. More from Phil on Sixty Symbols: bit.ly/C_SixtySym Silicon brain: https://youtu.be/2e06C-yUwlc Thanks to Noah Hardwicke for the Chr
From playlist Professor Moriarty - Sixty Symbols
Stéphane Nonennmacher - From Fractal Weyl Laws to spectral questions on sparse directed graphs
https://indico.math.cnrs.fr/event/3475/attachments/2180/2563/Nonnenmacher_GomaxSlides.pdf
From playlist Google matrix: fundamentals, applications and beyond
Henry Adams (6/2/20): From persistent homology to machine learning
Title: From persistent homology to machine learning Abstract: I will give an overview of a variety of ways to turn persistent homology output into input for machine learning tasks, including a discussion of the stability and interpretability properties of these methods. Persistent homolog
From playlist SIAM Topological Image Analysis 2020
Random Walks from Einstein to the Present - Thomas Spencer
Public Lecture: Thomas Spencer Institute for Advanced Study December 1, 2005 More videos on http://video.ias.edu
From playlist Mathematics
What are fractals? Just look at your broccoli to find out! License: Creative Commons BY-NC-SA More information at http://k12videos.mit.edu/terms-conditions
From playlist Measurement