joshspeagle

dynesty

Dynamic Nested Sampling package for computing Bayesian posteriors and evidences

brutus

Modeling stellar photometry with "brute force" methods

frankenz

A photometric redshift monstrosity

aparture

An LLM-powered tool to help sift through the arxiv

allsky

3-D visualization of galactic motion

nrp_astrobayes

Code and data for the example shown in Eadie et al. (2023)

typical_sets

Outlining the role of typical sets in (MCMC) sampling

arxivy

Helping to keep up with the arXiv

astrostat_uoft

Astrostatistics Research Team (ART) Website

AY191

Statistical exercises for Astronomy 191 (Spring 2019) at Harvard

exopop

Inferring the population of exoplanets

harvardastro_MLJC

phot_bias

Biases in Maximum-Likelihood Photometry

UCSC-Python-Coffee

Simple demonstration of scikit-learn for Python Coffee at UCSC on 12/8/2016.

bio-cv

curriculum vitae

joshspeagle.github.io

Personal website

nestle

Pure Python, MIT-licensed implementation of nested sampling algorithms for evaluating Bayesian evidence.

PCAT

Probabilistic Cataloging

prospector

Python code for Stellar Population Inference from Spectra and SEDs

research

research projects

savelli-kustec-gal-sfh

Repository containing the data and code used in Savelli & Kustec et al. (in prep.).

STA130-W23

Files for STA130 for the 2023 Winter Term at the University of Toronto

STA130_ProblemSet8-Week10

Fall 2022 STA130 (Week 10) Problem Set 8 (Due 5 p.m. ET Thursday)