Участник:Strijov/Drafts
Материал из MachineLearning.
(Различия между версиями)
(→Fourier for fun and practice nD) |
(→Theme 1: PDE) |
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*[https://arxiv.org/pdf/1505.05770.pdf Variational Inference with Normalizing Flows (source paper)] | *[https://arxiv.org/pdf/1505.05770.pdf Variational Inference with Normalizing Flows (source paper)] | ||
*[https://lilianweng.github.io/lil-log/2018/10/13/flow-based-deep-generative-models.html Flow-based deep generative models] | *[https://lilianweng.github.io/lil-log/2018/10/13/flow-based-deep-generative-models.html Flow-based deep generative models] | ||
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| + | (after RBF) | ||
==Theme 1: PDE== | ==Theme 1: PDE== | ||
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| + | ==Theme 1: Navier-Stokes equations and viscous flow== | ||
== Fourier for fun and practice 1D== | == Fourier for fun and practice 1D== | ||
Версия 20:11, 1 августа 2021
- 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
- Neural Ordinary Differential Equations (source paper and code)
- W: Flow-based generative model
- Flows at deepgenerativemodels.github.io
- Знакомство с Neural ODE на хабре
Goes to BME
(after RBF)
Theme 1: PDE
Theme 1: Navier-Stokes equations and viscous flow
Fourier for fun and practice 1D
Fourier for fun and practice nD
See:
- Fourier analysis on Manifolds 5G page 49
- Spectral analysis on meshes
Geometric Algebra
experior product and quaternions
Theme 1: High order splines
Theme 1: Topological data analysis
Theme 1: Homology versus homotopy
