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    Explorers Group: TF 2.X and PyTorch for not so Dummies
    
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- Numpy
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Talks
Talks
Thesis
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- Toc
- Chapters
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  - 1 introduction
    1 introduction
    
    Earth Science Setting
    
    Machine Learning Setting
    
    1.3 thesis
  - 2 models
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    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
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    TODO
  - 5 applications
    5 applications
    
    Sensitivity Applications
    
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    Uncertainty Applications
Tutorials
Tutorials
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    Resources
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- Manifold learning
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- Pytorch nns
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- Remote computing
  Remote computing
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