
Informed Source Separation: A Bayesian Tutorial
Source separation problems are ubiquitous in the physical sciences; any ...
11/13/2013 ∙ by Kevin H. Knuth, et al. ∙ 0 ∙ shareread it

Bitwise Source Separation on Hashed Spectra: An Efficient Posterior Estimation Scheme Using Partial Rank Order Metrics
This paper proposes an efficient bitwise solution to the singlechannel ...
08/22/2017 ∙ by Lijiang Guo, et al. ∙ 0 ∙ shareread it

Bayesian Deep Learning for Exoplanet Atmospheric Retrieval
Over the past decade, the study of exoplanets has shifted from their det...
11/08/2018 ∙ by Frank Soboczenski, et al. ∙ 0 ∙ shareread it

A Hierarchical Bayesian Approach to Neutron Spectrum Unfolding with Organic Scintillators
We propose a hierarchical Bayesian model and stateofart Monte Carlo sa...
09/09/2019 ∙ by Haonan Zhu, et al. ∙ 0 ∙ shareread it

Multichannel Linear Prediction for Blind Reverberant Audio Source Separation
A class of methods based on multichannel linear prediction (MCLP) can ac...
02/24/2017 ∙ by Ilker Bayram, et al. ∙ 0 ∙ shareread it

A Novel CMB Component Separation Method: Hierarchical Generalized Morphological Component Analysis
We present a novel technique for Cosmic Microwave Background (CMB) foreg...
10/17/2019 ∙ by Sebastian WagnerCarena, et al. ∙ 0 ∙ shareread it

Nearest Neighbor SearchBased Bitwise Source Separation Using Discriminant WinnerTakeAll Hashing
We propose an iterationfree source separation algorithm based on Winner...
08/26/2019 ∙ by Sunwoo Kim, et al. ∙ 0 ∙ shareread it
Bayesian Source Separation Applied to Identifying Complex Organic Molecules in Space
Emission from a class of benzenebased molecules known as Polycyclic Aromatic Hydrocarbons (PAHs) dominates the infrared spectrum of starforming regions. The observed emission appears to arise from the combined emission of numerous PAH species, each with its unique spectrum. Linear superposition of the PAH spectra identifies this problem as a source separation problem. It is, however, of a formidable class of source separation problems given that different PAH sources potentially number in the hundreds, even thousands, and there is only one measured spectral signal for a given astrophysical site. Fortunately, the source spectra of the PAHs are known, but the signal is also contaminated by other spectral sources. We describe our ongoing work in developing Bayesian source separation techniques relying on nested sampling in conjunction with an ON/OFF mechanism enabling simultaneous estimation of the probability that a particular PAH species is present and its contribution to the spectrum.
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