Juan Emmanuel Johnson

gp_model_zoo. Literature and light wrappers for gaussian process models.

research_journal. My Research Journal covering various topics that interest me. They're mostly scattered notes and resources.

uncertain_gps. Exploring how to to deal with uncertain inputs with gaussian process regression models.

oceanbench. OceanBench - SSH edition

research_notebook. My personal research notebook with notes, tutorials, and resources written in Jupyterbook.

xrpatcher. A ML-oriented generic patcher for xarray data structures.

jaxsw. Simple differentiable approximate ocean models built with JAX.

somax. Simple Ocean Models with JAX

manifold_learning. A repository with work-in-progress code: Schroedinger Eigenmaps for Manifold Learning

ml4ssh. Machine learning applied to interpolate sea-surface height observations from altimetry tracks.

finitevolX. Finite Volume tools in JAX

pysim. A package for using similarity measures like HSIC using python.

kernellib. A simple package with all of my kernel functions.

research_journal_v2. Jupyter Notebook

rbig. Rotation-Based Iterative Gaussianization (RBIG) - a gaussianization algorithm with information measures.

rbig_eo. Using RBIG and the IT measures for analyzing Earth Observation and climate data.

dot_files. My dot files that I often use for in my computing day-to-day life.

ocn-tools. Ocean Utility tools for working with oceanbench.

geo_toolz. Jupyter Notebook

manipy. My manifold learning library of semisupervised extensions.

website_academic. My academic website built with quarto.

jejeqx. My models that I look at to test out JAX.

nerf4ssh. Neural Fields for Sea Surface Height Interpolation.

jbayesevt. Bayesian Modeling for Extreme Values: Applications to Climate Attribution

hsi_python. hyperspectral image routines with python.

rs_tools. Jupyter Notebook

jaxkf. Kalman Filters with Modern ML methods.