Research notes

Scarlet2 – Thoughts for a major redesign
Astronomical source modeling and separation, all new and shiny
Bayesian inference three ways
Running MCMC, Hamiltonian MC, and simulation-based inference with a few lines of code
Proximal matrix factorization in pytorch
Constrained optimization with autograd
Data Science in Astronomy: pyTorch introduction
Neural networks without clutter
Data Science in Astronomy: Neural networks 101
The structure and power of shallow networks for regression and classification
Data Science in Astronomy: Classification Theory
The common ideas behind classification with Naive Bayes, LDA, QDA, logit, and SVM
Data Science in Astronomy: Clustering
Clustering of cluster galaxies with K-means, Mean-Shift, MST, and the Gap statistic
Data Science in Astronomy: Introduction and scikit-learn
An overview of jargon, plus multi-band detection by clustering in color space
The magic of proximal operators
Constrained optimization made easy
Gaussian mixture models for Astronomy
An intro for observational data analysis projects
Map projections for wide-field surveys
What cartography can teach us about survey visualization
Four massive clusters from DES SV data
We went out to test DECam, and got galaxy clusters and filaments