Gaia science performance simulation toolkit

A multi-planet Radial Velocity and Transit modelling software

Create Your Own Metropolis-Hastings Markov Chain Monte Carlo Algorithm for Bayesian Inference (With Python)

Tools for data-driven spectra models with Gaussian processes. Pronounced "soap."

Better Radial velocities from Stellar Spectroscopy via Machine Learning

Apply the Nested Sampling Monte Carlo algorithm to fit exoplanet radial velocity data and estimate the posterior distribution of the model parameters

Scalpels algorithm

A testbed for stellar granulation in exoplanet RV searches.

A not so mini implementation of the Gaussian process frameworks described on Rajpaul et al. (2015) and Jones et al. (2017).

Computes Cross Correlation Functions (CCFs) with RvSpectML

Decompose spectrum of resolved SB2 binary to extract radial velocity of individual components

General Toolkit for Modeling Radial Velocities

Statistical tools for Combined Analysis of Radial Velocity Signals

Base package to be imported by other members of RvSpectML ecosystem

Using the radial velocity method to find the semi-major axis and mass of planets

Modelling RV and activity indicators with an artificial GP network

Jupyter Notebooks for the radial velocity tutorials at the Precision Spectroscopy Workshop 2017, held at the Instituto de Astronomia, Geofísica e Ciências Atmosféricas (Universidade de São Paulo) in August 2017.

Using Monte Carlo Methods to estimate mass potential parameters on a model describing a galaxy radial velocity in terms of the radius with the bayesian parameter estimation.

A pure Python code for working with radial velocities of stars with a massive companion.

The use of Gaussian processes in the analysis of radial velocity measurements if you are into those things.