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A small fraction of the gravitational-wave (GW) signals from binary black holes observable by ground-based detectors will be strongly lensed by intervening objects such as galaxies and clusters. Strong lensing will produce nearly identical…

General Relativity and Quantum Cosmology · Physics 2024-12-03 A. Barsode , S. Goyal , P. Ajith

When statistical analyses consider multiple data sources, Markov melding provides a method for combining the source-specific Bayesian models. Markov melding joins together submodels that have a common quantity. One challenge is that the…

Methodology · Statistics 2022-03-17 Andrew A. Manderson , Robert J. B. Goudie

Mixture models with Gamma and or inverse-Gamma distributed mixture components are useful for medical image tissue segmentation or as post-hoc models for regression coefficients obtained from linear regression within a Generalised Linear…

Machine Learning · Statistics 2016-07-27 A. Llera , D. Vidaurre , R. H. R. Pruim , C. F. Beckmann

In this paper, we consider sampling from a class of distributions with thin tails supported on $\mathbb{R}^d$ and make two primary contributions. First, we propose a new Metropolized Algorithm With Optimization Step (MAO), which is well…

Machine Learning · Statistics 2021-12-02 EL Mahdi Khribch , George Deligiannidis , Daniel Paulin

We study the computational complexity of a Metropolis-Hastings algorithm for Bayesian community detection. We first establish a posterior strong consistency result for a natural prior distribution on stochastic block models under the…

Statistics Theory · Mathematics 2018-11-08 Bumeng Zhuo , Chao Gao

This paper presents a new modeling strategy for joint unsupervised analysis of multiple high-throughput biological studies. As in Multi-study Factor Analysis, our goals are to identify both common factors shared across studies and…

Applications · Statistics 2018-06-27 Roberta De Vito , Ruggero Bellio , Lorenzo Trippa , Giovanni Parmigiani

Upcoming space-based gravitational-wave detectors will be sensitive to millions and resolve tens of thousands of stellar-mass binary systems at mHz frequencies. The vast majority of these will be double white dwarfs in our Galaxy. The…

High Energy Astrophysical Phenomena · Physics 2025-08-21 Riccardo Buscicchio , Antoine Klein , Valeriya Korol , Francesco Di Renzo , Christopher J. Moore , Davide Gerosa , Alessandro Carzaniga

We present an accelerated pipeline, based on high-performance computing techniques and normalizing flows, for joint Bayesian parameter estimation and model selection and demonstrate its efficiency in gravitational wave astrophysics. We…

Instrumentation and Methods for Astrophysics · Physics 2024-11-01 Alicja Polanska , Thibeau Wouters , Peter T. H. Pang , Kaze K. W. Wong , Jason D. McEwen

We present a novel algorithm aimed at identifying peaks within a uniformly sampled time series affected by uncorrelated Gaussian noise. The algorithm, called "MEPSA" (multiple excess peak search algorithm), essentially scans the time series…

Instrumentation and Methods for Astrophysics · Physics 2015-01-07 C. Guidorzi

We describe several new techniques which accelerate Bayesian searches for continuous gravitational-wave emission from supermassive black-hole binaries using pulsar timing arrays. These techniques mitigate the problematic increase of…

General Relativity and Quantum Cosmology · Physics 2014-11-25 Stephen Taylor , Justin Ellis , Jonathan Gair

Using a nested sampling analysis, we study the gravitational-wave background (GWB) predicted by the Gasperini--Veneziano model of pre-big-bang cosmology, both in its most recent minimal and non-minimal versions. Within the LISA sensitivity…

General Relativity and Quantum Cosmology · Physics 2026-05-20 Xoán Vilas Currás , Gianluca Calcagni

We consider the inverse Ising problem, i.e. the inference of network couplings from observed spin trajectories for a model with continuous time Glauber dynamics. By introducing two sets of auxiliary latent random variables we render the…

Machine Learning · Statistics 2017-12-22 Christian Donner , Manfred Opper

The future space-based gravitational-wave detector LISA will deliver rich and information-dense data by listening to the milliHertz Universe. The measured time series will contain the imprint of tens of thousands of detectable Galactic…

General Relativity and Quantum Cosmology · Physics 2022-04-27 Quentin Baghi

Humans are very good at optimizing solutions for specific problems. Biological processes, on the other hand, have evolved to handle multiple constrained distributed environments and so they are robust and adaptable. Inspired by observations…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-03-19 Yehuda Afek , Noga Alon , Ziv Bar-Joseph

Efficient symbol detection algorithms carry critical importance for achieving the spatial multiplexing gains promised by multi-input multi-output (MIMO) systems. In this paper, we consider a maximum a posteriori probability (MAP) based…

Information Theory · Computer Science 2017-10-04 Yavuz Yapici , Ismail Guvenc , Yuichi Kakishima

Linear discriminant analysis (LDA) is a fundamental classification and dimension reduction method that achieves Bayes optimality under Gaussian mixture, but often struggles in high-dimensional settings where the covariance matrix cannot be…

Computation · Statistics 2026-04-06 Cencheng Shen , Yuexiao Dong

Gravitational waves from the inspiral and coalescence of supermassive black-hole (SMBH) binaries with masses ~10^6 Msun are likely to be among the strongest sources for the Laser Interferometer Space Antenna (LISA). We describe a…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Duncan A. Brown , Jeff Crowder , Curt Cutler , Ilya Mandel , Michele Vallisneri

The Laser Interferometer Space Antenna (LISA) will feature a prominent anisotropic astrophysical stochastic gravitational wave signal, arising from the tens of millions of unresolved mHz white dwarf binaries in the Milky Way: the Galactic…

Instrumentation and Methods for Astrophysics · Physics 2025-01-27 Alexander W. Criswell , Steven Rieck , Vuk Mandic

Scientists often must simultaneously localize and discover signals. For instance, in genetic fine-mapping, high correlations between nearby genetic variants make it hard to identify the exact locations of causal variants. So the statistical…

Methodology · Statistics 2023-01-31 Asher Spector , Lucas Janson

Scientists often express their understanding of the world through a computationally demanding simulation program. Analyzing the posterior distribution of the parameters given observations (the inverse problem) can be extremely challenging.…

Machine Learning · Computer Science 2014-01-14 Edward Meeds , Max Welling
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