ML4EO

In this section, we will look at some of the staple methods for nonparametric interpolation. We will outline each

• Naive Whirlwind Tour with applications for Data Assimilation

• Nearest Neighbours

  • K-NN

  • Weighted Distances

  • Scaling the Algorithm - KDTree + BallTree

  • Scaling the hardware - parallelization, GPU hardware

• Kernel Density Estimation

  • KDE

  • FFT for Equidistant Grids

  • scaling the hardware - GPU hardware

  • Regression

• Gaussian Processes

  • Appendix: Playing with All things Gaussian

  • Spatial Autocorrelation with (Semi-)Variograms

  • 3 Views of GPs

  • GP with Numpyro

  • Scaling - Kernel Approximations

  • Scaling - Inducing Points

  • Scaling -

  • Appendix GPs in practice

    • From Scratch

    • With TinyGP & GPJax

    • With PPL Numpyro

    • Customizing the Numpyro Implementation

    • Distances

    • Kernel Matrices

    • Kernel Matrix Derivatives

• Improved Gaussian Processes

  • Moment-Based

    • Sparse GPs

    • SVGPs

    • Structured GPs

    • Deep Kernel Learning

  • Basis Functions

    • Fourier Features GP

    • Spherical Harmonics GP

    • Sparse Spherical Harmonics GPs