Empirical Inference

Dingo (Deep Inference for Gravitational-wave Observations)


Dingo (Deep Inference for Gravitational-wave Observations) is a Python program for analyzing gravitational wave data using neural posterior estimation. It dramatically speeds up inference of astrophysical source parameters from data measured at gravitational-wave observatories. Dingo aims to enable the routine use of the most advanced theoretical models in analysing data, to make rapid predictions for multi-messenger counterparts, and to do so in the context of sensitive detectors with high event rates.

Author(s): Maximilian Dax, Stefen Green, Michael Pürrer, Nihar Gupte, Jonas Wildberger
Department(s): Empirical Inference
Research Projects(s): Astronomy
Authors: Maximilian Dax, Stefen Green, Michael Pürrer, Nihar Gupte, Jonas Wildberger
License: The MIT License (MIT)
Repository: https://github.com/dingo-gw/dingo
Documentation: https://dingo-gw.readthedocs.io