Name: Gregory Green
Type: User
Company: Max Planck Institute for Astronomy
Bio: Sofia Kovalevskaya Group Leader at the Max Planck Institute for Astronomy. Former postdoc at KIPAC, Stanford. PhD in Astronomy and Astrophysics from Harvard.
Location: Heidelberg, Germany
Blog: greg.ory.gr/een
Gregory Green's Projects
Anki for desktop computers
Various small tools to use alongside Anki.
Bayesian photometric parallax. Infers distances, reddenings, stellar types, and line-of-sight extinction profiles.
Annual computing Boot Camp for new (and other) KIPAC members
Combinatorial space sampler using bridging, based on Lin & Fisher (2012).
Simple divide-and-conquer algorithm for crossmatching catalogs, using a HEALPix partitioning of the sky.
Data-driven stellar spectral energy distributions.
Utilities for interacting with the Dataverse.
simple decam observation planner (borrowing heavily from A. Patej's nightlystrategy.py)
Deep learning for gravitational potentials, based on well-mixed tracers in phase space.
Beautiful Word and LaTeX dissertation templates.
Simple 2D projection code for a Bayestar-like 3D dust map.
A uniform interface for a number of 2D and 3D maps of interstellar dust reddening/extinction.
Various exploitations of the IEEE 754 floating-point standard.
Forward model of the Gaia XP spectra, learned directly from the data.
Bayesian inference of stellar parameters
Git Cheatsheet
Google translate as Python module & command line tool. No key, no authentication whatsoever.
Data-driven model of stellar photometry, as described in Green+(2020).
Personal website on GitHub
Utility functions for the HDF5 C++ API. These mostly get around some of the annoyances of the original API, such as the frequent exceptions it throws, and the many steps necessary to create a vanilla dataset or group.
Draw a HEALPix map to an HTML5 canvas.
Bayesian Inference on Milky Way Datasets
High-Galactic-latitude 2D dust map using Gaussian Processes.
An example of how to make a fancy scientific talk in HTML
Hybrid Monte Carlo implementation
A dust map based on HI column densities and stellar reddenings.
Software and datasets for the astrostatistics workshop portion of the Local Group Astrostatistics Conference 2015
Utilities for working with image data, text data, and sequence data.