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Modeling data with correlated errors across a directed graph
Using PyMC to model data with DAG-structured error correlations
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To my junior collaborators, this is how I want you to write your research code
Opinionated commentary on making a data cleaning script for research
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Solving climate change by abusing thermodynamic scaling laws
A wintertime climate change solution
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Modeling temporal data with an unknown number of changepoints
A nonparametric changepoint model in PyMC
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Distributed zonal averages for fast geospatial analyses
Easy local average with Google Earth Engine's Python API
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Fast Kronecker matrix-vector product with einsum
Easy local average with Google Earth Engine's Python API
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Balanced spatial partitioning for point data in 20 lines
Recursively splitting by boxes
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Modeling spatial structure in binary data with an H3 hexagonal coordinate system
Conditional autoregression for 6-adjacent data
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Surrogate modeling for SEIR dynamics
Modeling a model, for epidemiology
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Density estimation for geospatial imagery using autoregressive neural models
Conditional autoregression for 6-adjacent data