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Overview
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Explorers
Explorers
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- BNNs
  BNNs
  - Bayesian Neural Networks Working Group
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    My notes
    
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    Other
    
    Explorers Group: TF 2.X and PyTorch for not so Dummies
    
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    Prezis
    
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  - Theory
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Appendix
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- Bayesian
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  - Generative Modeling
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    Flows
    
    Applications in Earth Science
    
    Gaussinization
    
    HouseHolder Flows
    
    Normalizing Flows Literature
    
    Continuous Mixture CDFs
  - Gaussianization
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    RBIG for Spatial-Temporal Representation Analysis
    
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    Unscented Transformation
    
    Applications
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    Climate
    
    Demo: Gaussianization
    
    Drought
    
    Spatial temporal
    
    Software
    Software
    
    Coupling Layers
    
    Loss Functions
    
    Marginal Gaussianization
    
    Marginal Uniformization
    
    Refactoring RBIG (RBIG 1.1)
    
    Rotation
    
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    Theory
    
    Gaussianization
    
    Information Theory Measures
    
    Literature Review
    
    Related Methods
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    Overview
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    Similarity Measures
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Snippets
Snippets
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  - Error in GPs in Sklearn
- Earth
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  - Cartesian Coordinates 2 Geocoordinates
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- Numpy
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Talks
Talks
Thesis
Thesis
- My Thesis
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- My Thesis: A Overview
- Toc Toc
  Table of contents
  - Data Representations
- Chapters
  Chapters
  - 1 introduction
    1 introduction
    
    Earth Science Setting
    
    Machine Learning Setting
    
    1.3 thesis
  - 2 models
    2 models
    
    Sensitivity
    
    Similarity
    
    Uncertainty
  - 3 similarity
    3 similarity
    
    Hybrid Approaches
    
    Kernel Methods
    
    Neural Networks
    
    Randomized
  - 4 information
    4 information
    
    Density
    Density
    
    Overview
    
    Density Estimation
    
    Parametric Gaussianization
    
    Normalizing Flows
    
    Parametric
    
    Rotation-Based Iterative Gaussianization (RBIG)
    
    Information
    Information
    
    Information Theory
    
    TODO
  - 5 applications
    5 applications
    
    Sensitivity Applications
    
    Similarity Applications
    
    Uncertainty Applications
Tutorials
Tutorials
- Tutorials
- Earth sci
  Earth sci
- Gaussian processes
  Gaussian processes
  - ideas
- Jax
  Jax
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  - Bisection search
  - Classes
  - Ecosystem
  - Jax Tutorial Ideas
  - Init funcs
  - Jit
  - Optimizing Using Jax
  - VMAP
  - Lab tutorials
    Lab tutorials
    
    Bandwidth Approximation
    
    Kernel Derivatives
    
    Kernel Matrices
    
    MonteCarlo
    
    Pairwise
    
    Resources
- Jupyter vscode
  Jupyter vscode
  - Using Jupyter Notebooks for VSCode Remote Computing
- Manifold learning
  Manifold learning
  - Semisupervised Manifold Alignment
  - 6 laplacian eigenmaps
- Pytorch nns
  Pytorch nns
- Remote computing
  Remote computing
- Tf2
  Tf2
  - Slides
  - Docs
    Docs
    
    Css
    Css
    
    Theme
    Theme
    
    Index
    
    Plugin
    Plugin
    
    Markdown
    Markdown
    
    Markdown Demo

Table of contents

Data Representations

Toc

Data Representations¶

Features
Neural Networks
Probabilistic Neural Networks

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