Max Joseph
mbjoseph
AI + Earth Observation + Bayesian stats
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145
Stars
204
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62
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R
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Top Repositories
Conditional autoregressive models in Stan
Code for the paper "Neural hierarchical models of ecological populations"
Spatial capture-recapture models in Stan
R package to scrape data from basketball-reference.com
academic article template w/ knitr, R Markdown, and pandoc
Training material: how and why to make a research compendium
Repositories
145Spatial capture-recapture models in Stan
Conditional autoregressive models in Stan
R package to scrape data from basketball-reference.com
Code for the paper "Neural hierarchical models of ecological populations"
Training material: how and why to make a research compendium
No description provided.
Exploratory analysis of Bayesian models with Python
Spatiotemporal modeling of wildfire extremes
Visualizing numbers and their factors with circles
Simulations for generating & Bayesian model for analysing capture-recapture data
An R Package for Hierarchical Bayesian Analysis of North American Breeding Bird Survey Data
A research compendium for: “Using visual encounter data to improve capture-recapture abundance estimates”
academic article template w/ knitr, R Markdown, and pandoc
MLFlow with cmdstanr
Introduction to parallel R - CU Computational Science and Engineering meetup
Stan website based on the So Simple Jekyll theme.
R script to fetch MTBS fire data, EPA ecoregion boundaries, and some MACA climate data
Slides from an introduction to git tutorial
Material for teaching coding style and practices for scientific computing
No description provided.
This is a demo repo for a git training workshop
Hyperspectral beta diversity vs. in situ beta diversity: same same or different?
Slides and scripts for teaching linear models in R
Introduction to functions in R
No description provided.
Example of using profiling with stantargets
Turn xarray timestacks into GIFs
Introduction to extreme value analysis in R
No description provided.
Mulitlevel modeling with detection error correction. Blog for Ecology in silico