andersdot Goto Github PK

andersdot.github.io

my personal website

astr599_homework

Repository for students to submit homework assignments as pull requests

bigreds

bring-devops-to-machine-learning-with-cml

Leveraging the powerful features of DevOps like CI/CD, automation, workflows and apply them to our data science projects & experiments with MLOps. The CML – Continuous Machine Learning is a very handy tool have for tracking the experiment results, collaborate with others, and automating the entire workflow.

calculatorlibrary

chempy

Start with the Chempy tutorial

cml_base_case

dust

infer 3D dust map from noisy distance and integrated dust values

dustm31

Data-driven inferences of dust in the Andromeda Galaxy

energy-forecasting

Compare forecasting models of energy production and needs

extinctions

Inferring extinctions for millions of stars in the Milky Way galaxy

gaiadr2

highmetallicityhalo

Search for structures in the high metallicity stars in the Milky Way halo

lf

analysis software for creating luminosity functions from ChaNGa simulations

lya-invertphase

A method to reduce unwanted sample variance when predicting Lya forest power spectra, which converges 30x faster enabling tractable inference of cosmological parameters

mockstreams

Mock observe disrupted globular clusters with Gaia errors

modelmwkinematics

mp-gadget

massively-parallel cosmology simulator

nbodypythontools

Tools to analyze and explore large astronomical simulations of galaxy formation

pdp2018

Materials for teaching the Akamai interns as part of the 2018 PDP program

photoparallax

data-driven photometric parallaxes, built with Gaia and 2MASS

radialmigration

Testing the radial migration of stars using Gaia and Apogee

shoderivz

Speeding up inferences that include evolving physical systems

stellarspec

stellartwins

theorycmd

Fitting a theoretical cmd with a normalizing flow

thesis

The Little Galaxies that could Reionize the Universe

wids2023_mi_team4e

WIDS Datathon 2023