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Found 5 papers, 1 papers with code
GALILEO: A Generalized Low-Entropy Mixture Model
We present a new method of generating mixture models for data with categorical attributes.
Bayesian Learning of Clique Tree Structure
The problem of categorical data analysis in high dimensions is considered.
Robust parameter estimation for compact binaries with ground-based gravitational-wave observations using the LALInference software library
We show that our implementation is able to correctly recover the parameters of compact binary signals from simulated data from the advanced GW detectors.
General Relativity and Quantum Cosmology High Energy Astrophysical Phenomena Instrumentation and Methods for Astrophysics
SKYNET: an efficient and robust neural network training tool for machine learning in astronomy
We present the first public release of our generic neural network training algorithm, called SkyNet.
BAMBI: blind accelerated multimodal Bayesian inference
In this paper we present an algorithm for rapid Bayesian analysis that combines the benefits of nested sampling and artificial neural networks.
