Участник:Strijov/Drafts

Материал из MachineLearning.

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(Theme 1: Surface differential geometry)
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==Theme 1: Surface differential geometry ==
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==Theme 1: Manifolds ==
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==Code==
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Surface differential geometry
[https://www.coursera.org/lecture/image-processing/3-surface-differential-geometry-duration-11-43-vtuJ1 Coursera code video] for Image and Video Processing
[https://www.coursera.org/lecture/image-processing/3-surface-differential-geometry-duration-11-43-vtuJ1 Coursera code video] for Image and Video Processing
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==Theme 1: ODE and flows==
==Theme 1: ODE and flows==

Версия 19:46, 1 августа 2021

Содержание

  • Geometric deep learning
  • Functional data analysis
  • Applied mathematics for machine learning


General principles

1. The experiment and measurements defines axioms i


Syllabus and goals

Theme 1:

Message

Basics

Application

Code

https://papers.nips.cc/paper/2018/file/69386f6bb1dfed68692a24c8686939b9-Paper.pdf


Theme 1: Manifolds

Code

Surface differential geometry Coursera code video for Image and Video Processing

Theme 1: ODE and flows

Goes to BME

Theme 1: PDE

(after RBF)


Fourier for fun and practice 1D

Fourier Code



Fourier for fun and practice nD

Geometric Algebra

experior product and quaternions


Theme 1: High order splines

Theme 1: Topological data analysis

Theme 1: Homology versus homotopy

W: Homology



Fundamental theorems

W: Inverse function theorem and Jacobian

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