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Publications funded by COST must be a direct result of work performed by Action Participants and must be co-authored by Action Participants representing at least 3 different Participating COST Full Members / COST Cooperating Members. Whenever possible, publications should be made available under Open Access licences. Publications resulting from work performed by COST Action Participants fall under two distinct categories that are funded differently:

1. Publications produced during an Action’s lifetime funded under the CGS – sourced from the COST Grant and paid for by the Action’s Grant Holder

Once the article is accepted, please contact the Grant Holder for more information.

Talks and Posters

LIGO – Virgo meeting, Copernicus Conference Centre (CNK), Warsaw, Poland
Date: 2-5/09/2019

        • Antoni Ramos, Maite Mateu, Geraint Pratten, Héctor Estellés, Rafel Jaume, Cecilio García, Marta Colleoni, Sascha Husa.
          Numerical relativity waveform catalog, hybridization and parameter estimation of eccentric spinning black-hole binaries.
        • Cecilio García, Marta Colleoni, Gerain Pratten, Héctor Estellés, Sascha Husa, Antoni Ramos, Rafel Jaume, Maite Mateu.
          IMRPhenomXHM: Waveform model calibrated to multimode Hybrids with accelerated evaluation.
          Poster. LAAC Poster Prize:
        • Pep B. Covas, Alicia M. Sintes.
          New method to search for continuous gravitational waves from unknown neutron stars in binary systems.
        • Héctor Estellés, Antoni Ramos, Cecilio García, Sascha Husa, Leïla Haegel, Rafel Jaume.
          PhenomT: a time domain phenomenological model for CBC signals.

GR22 – Amaldi13 conference:

        • Agata Trovato.
          Machine Learning to exploit LIGO Scientific Collaboration – EGO & the Virgo Collaboration single-detector data taking periods.
        • Alessio Cirone.
          Newtonian noise cancellation with Deep Learning.
        • Filip Morawski.
          Deep Learning classification of the gravitational – wave signal candidates from the time-domain F-statistic search.
        • Alba Romero Rodríguez.
          A convoluted neural network implementation for the search for compact binary signals at Virgo.
        • Alberto Less.
          Machine-Learning Classification of Core-Collapse Supernovae.
        • Rodrigo Tenorio, Miquel Oliver, Alicia M. Sintes.
          Noise-Robust Strategies For Continuous Gravitational Wave Searches: Improvements On The Skyhough All-Sky Search.

1st Real Time Analysis Workshop:
Elena Cuoco.
Real Time Classifier for Gravitational Wave Signals.

Artificial Intelligence in Astronomy Workshop at ESO:
Filip Morawski
Deep learning classification of the gravitational-wave signal candidates from the time-domain F-statistic search.

Hammers & Nails 2019. Machine Learning Meets Astro & Particle Physics:
Elena Cuoco
Gravitational Waves and ML.

SpliTech Conference
Jonatan Lerga.
Denoising Accuracy of Adaptive ICI-Based Estimators With Regards to Sampling Rate.
Talk [+].

2020 Accelerated Artificial Intelligence for Big-Data Experiments Conference:
Agata Trovato.
Neural Networks for Gravitational-Wave Trigger Selection in Single-Detector Periods.
Talk (Video) [+].
Talk (Slides) [+].

EGU General Assembly 2020:
Velimir Ilić.
Ambient seismic noise suppression in COST action G2Net:
Talk. GI – Geosciences Instrumentation & Data Systems.

PhD Thesis

Miquel Oliver Almiñana, Universitat de les Illes Balears
July 31st, 2019
Gravitational wave data analysis for the advanced detector era.
Supervisors: Dr. Alicia M. Sintes Olives, Dr. Sascha Husa.

Antoni Ramos Buades, Universitat de les Illes Balears
July 21th, 2020
Gravitational waves from generic binary black holes: From numerical simulations to observational results.
Supervisor: Dr. Sascha Husa.

Cecilio García Quirós, Universitat de les Illes Balears
July 22th, 2020
Waveform modelling of Binary Black Holes in the Advanced LIGO era.
Supervisors: Dr. Sascha Husa, Dr. Alicia M. Sintes Olives.

Josep Blai Covas Vidal, Universitat de les Illes Balears
July 28th, 2020
Searching for continuous gravitational waves with Advanced LIGO.
Supervisor: Dr. Alicia M. Sintes Olives.

Alessio Cirone, University of Genova
Mar 23, 2020
Magnetic and Newtonian noises in Advanced Virgo: evaluation and mitigation strategies.
Supervisors: Andrea Chincarini, Maurizio Canepa.

Alberto Iess, Universty of Rome Tor Vergata
Apr 19, 2021
Deep Learning for Core-Collapse Supernova Gravitational Wave Signals and Noise Transient
Supervisors: Prof. Viviana Fafone Dr. Elena Cuoco

Nikola Lopac, University of Rijeka, Faculty of Engineering
March 11th, 2022
Detection of Gravitational-Wave Signals from Time- Frequency Distributions Using Deep Learning
Supervisor: Prof. Dr. Jonatan Lerga

Scientific Articles

BinarySkyHough: A new method to search for continuous gravitational waves from unknown neutron stars in binary systems.
P. B. Covas, Alicia M. Sintes.
Physical Review D 99, 124019 (2019). arXiv:1904.04873. DOI: 10.1103/PhysRevD.99.124019

The Adaptive Transient Hough method for long-duration gravitational wave transients.
Miquel Oliver, David Keitel, Alicia M. Sintes.
Physical Review D 99, 104067 (2019). arXiv:1901.01820. DOI: 10.1103/PhysRevD.99.104067

Matched-filter study and energy budget suggest no detectable gravitational-wave ‘extended emission’ from GW170817.
Miquel Oliver, David Keitel, Andrew L. Miller, Hector Estelles, Alicia M. Sintes.
Monthly Notices of the Royal Astronomical Society, Volume 485, Issue 1 (2019). arXiv:1812.06724. DOI: 10.1093/mnras/stz439

Generalized application of the Viterbi algorithm to searches for continuous gravitational-wave signals.
Joe Bayley, Chris Messenger, Graham Woan.
Physical Review D 100, 023006 (2019). arXiv:1903.12614. DOI: 10.1103/PhysRevD.100.023006

Deep-learning continuous gravitational waves.
Christoph Dreissigacker, Rahul Sharma, Chris Messenger, Ruining Zhao, Reinhard Prix.
Physical Review D 100, 044009 (2019). arXiv:1904.13291. DOI: 10.1103/PhysRevD.100.044009

Spectral classification of gravitational-wave emission and equation of state constraints in binary neutron star mergers.
Andreas Bauswein, Nikolaos Stergioulas.
Journal of Physics G: Nuclear and Particle Physics 46, 113002 (2019). arXiv:1901.06969. DOI: 10.1088/1361-6471/ab2b90

Long term measurements from the Mátra Gravitational and Geophysical Laboratory.
P. Ván et al.
The European Physical Journal Special Topics 228, 1693–1743 (2019). arXiv:1811.05198. DOI: 10.1140/epjst/e2019-900153-1

Seismic noise measures for underground gravitational wave detectors.
L. Somlai, Z. Gráczer, P. Lévai, M. Vasúth, Z. Wéber, P Ván.
Acta Geodaetica et Geophysica 54, 301–313 (2019). arXiv:1810.06252. DOI: 10.1007/s40328-019-00257-5

Adaptive Thresholding in Extracting Useful Information From Noisy Time- Frequency Distributions.
Nicoletta Saulig, Jonatan Lerga, Zlatko Baracskai, Miloš Daković.
11th International Symposium on Image and Signal Processing and Analysis (ISPA), Dubrovnik, Croatia, 329-334 (2019). DOI: 10.1109/ISPA.2019.8868836

Denoising Accuracy of Adaptive ICI-Based Estimators With Regards to Sampling Rate.
Jonatan Lerga, Nicoletta Saulig, Martina Žuškin, Ante Panjkota.
4th International Conference on Smart and Sustainable Technologies (SpliTech), Split, Croatia, 1-6 (2019). DOI: 10.23919/SpliTech.2019.8783082

Time-Frequency Analysis of Ionospheric Whistler Signals.
Miloš Daković, Milan Ponjavić, Isidora Stanković, Jonatan Lerga, Cornel Ioana.
27th Telecommunications Forum (TELFOR), Belgrade, Serbia, 1-4 (2019). DOI: 10.1109/TELFOR48224.2019.8971020

Machine-Learning Nonstationary Noise Out of Gravitational-Wave Detectors.
Gabriele Vajente, Yiwen Huang, Maximiliano Isi, Jenne C. Driggers, Jeffrey S. Kissel, Marek J. Szczepanczyk, Salvatore Vitale.
Physical Review D 101, 042003 (2020). arXiv:1911.09083. DOI: 10.1103/PhysRevD.101.042003

Scalable auto-encoders for gravitational waves detection from time series data.
Roberto Corizzo, Michelangelo Ceci, Eftim Zdravevski, Nathalie Japkowicz.
Expert Systems with Applications 151, 113378 (2020). DOI: 10.1016/j.eswa.2020.113378

First all-sky search for continuous gravitational-wave signals from unknown neutron stars in binary systems using Advanced LIGO data.
P. B. Covas, Alicia M. Sintes.
Physical Review Letters 124, 191102 (2020). arXiv:2001.08411. DOI: 10.1103/PhysRevLett.124.191102

Empirical relations for gravitational-wave asteroseismology of binary neutron star mergers.
Stamatis Vretinaris, Nikolaos Stergioulas, Andreas Bauswein.
Physical Review D 101, 084039 (2020). arxiv:1910.10856. DOI: 10.1103/PhysRevD.101.084039

Core-Collapse supernova gravitational-wave search and deep learning classification.
Alberto Iess, Elena Cuoco, Filip Morawski, Jade Powell.
Machine Learning: Science and Technology 1, 025014 (2020). arxiv:2001.00279 DOI: 10.1088/2632-2153/ab7d31

Rapid prediction of earthquake ground shaking intensity using raw waveform data and a convolutional neural network.
Dario Jozinović, Anthony Lomax, Ivan Štajduhar, Alberto Michelini .
Geophysical Journal International 222, 1379–1389 (2020). DOI: 10.1093/gji/ggaa233

Predicting the Properties of Black-Hole Merger Remnants with Deep Neural Networks.
L. Haegel, S. Husa.
Classical and Quantum Gravity 37, 13 (2020). arXiv:1911.01496. DOI: 10.1088/1361-6382/ab905c

Quantum fluctuations have been shown to affect macroscopic objects.
Valeria Sequino, Mateusz Bawaj.
Nature 583, 31-32 (2020). DOI: 10.1038/d41586-020-01914-4

Application of dictionary learning to denoise LIGO’s blip noise transients.
Alejandro Torres-Forné, Elena Cuoco, José A. Font, Antonio Marquina.
Physical Review D 102, 023011 (2020). arXiv:2002.11668. DOI: 10.1103/PhysRevD.102.023011

Bilinear noise subtraction at the GEO 600 observatory.
Nikhil Mukund et al.
Physical Review D 101, 102006 (2020). DOI: 10.1103/PhysRevD.101.102006

A Seismological Study of the Sos Enattos Area-the Sardinia Candidate Site for the Einstein Telescope.
Matteo Di Giovanni et al.
Seismological Research Letters (2020) DOI: 10.1785/0220200186

Search for strongly lensed counterpart images of binary black hole mergers in the first two LIGO observing runs.
Connor McIsaac, David Keitel, Thomas Collett, Ian Harry, Simone Mozzon, Oliver Edy, David Bacon.
Physical Review D 102, 084031, (2020). arXiv:1912.05389. DOI: 10.1103/PhysRevD.102.084031

Enhancing Gravitational-Wave Science with Machine Learning.
Elena Cuoco et al.
Machine Learning: Science and Technology (2020). arXiv:2005.03745. DOI: 10.1088/2632-2153/abb93a

IMRPhenomXHM: Multimode frequency-domain model for the gravitational wave signal from nonprecessing black-hole binaries.
Cecilio García-Quirós, Marta Colleoni, Sascha Husa, Héctor Estellés, Geraint Pratten, Antoni Ramos-Buades, Maite Mateu-Lucena, Rafel Jaume.
Physical Review D, 102, 064002 (2020). arXiv:2001.10914. DOI: 10.1103/PhysRevD.102.064002

Setting the cornerstone for a family of models for gravitational waves from compact binaries: The dominant harmonic for nonprecessing quasicircular black holes.
Geraint Pratten, Sascha Husa, Cecilio Garcia-Quiros, Marta Colleoni, Antoni Ramos-Buades, Hector Estelles, Rafel Jaume.
Physical Review D, 102, 064001 (2020). arXiv:2001.11412. DOI: 10.1103/PhysRevD.102.064001

Validity of common modelling approximations for precessing binary black holes with higher-order modes.
Antoni Ramos-Buades, Patricia Schmidt, Geraint Pratten, Sascha Husa.
Physical Review D, 101, 103014 (2020). arXiv:2001.10936. DOI: 10.1103/PhysRevD.101.103014

A first survey of spinning eccentric black hole mergers: numerical relativity simulations, hybrid waveforms, and parameter estimation.
Antoni Ramos-Buades, Sascha Husa, Geraint Pratten, Héctor Estellés, Cecilio García-Quirós, Maite Mateu, Marta Colleoni, Rafel Jaume.
Physical Review D 101, 083015 (2020). arXiv:1909.11011. DOI: 10.1103/PhysRevD.101.083015

Effects of proper motion of neutron stars on continuous gravitational-wave searches.
P. B. Covas
Monthly Notices of the Royal Astronomical Society, staa3624 (2020). arXiv:2007.08207. DOI: 10.1093/mnras/staa3624

Robust machine learning algorithm to search for continuous gravitational waves.
Joe Bayley, Chris Messenger, Graham Woan.
Physical Review D 102, 083024 (2020). arxiv:2008.00983. DOI: 10.1103/PhysRevD.102.083024

Detection and classification of supernova gravitational wave signals: A deep learning approach.
Man Leong Chan, Ik Siong Heng, Chris Messenger.
Physical Review D 102, 043022 (2020). arxiv:1912.13517. DOI: 10.1103/PhysRevD.102.043022

Enhancing the sensitivity of transient gravitational wave searches with Gaussian mixture models.
V. Gayathri, Dixeena Lopez, Pranjal R. S., Ik Siong Heng, Archana Pai, Chris Messenger.
Physical Review D 102, 104023 (2020). arxiv:2008.01262. DOI: 10.1103/PhysRevD.102.104023

A novel approach to extracting useful information from noisy TFDs using 2D local entropy measures.
Ana Vranković, Jonatan Lerga, Nicoletta Saulig.
EURASIP Journal on Advances in Signal Processing 18 (2020). DOI: 10.1186/s13634-020-00679-2

Improving the Performance of Dynamic Ship Positioning Systems: A Review of Filtering and Estimation Techniques.
Denis Selimović, Jonatan Lerga, Jasna Prpić-Oršić, Sasa Kenji.
Journal of Marine Science and Engineering 8, 234 (2020). DOI: 10.3390/jmse8040234

Deep Learning for Feature Extraction in Remote Sensing: A Case-Study of Aerial Scene Classification.
Biserka Petrovska, Eftim Zdravevski, Petre Lameski, Roberto Corizzo, Ivan Štajduhar, Jonatan Lerga.
Sensors 20, 3906 (2020). DOI: 10.3390/s20143906

Gravitational-Wave Burst Signals Denoising Based on the Adaptive Modification of the Intersection of Confidence Intervals Rule.
Nikola Lopac, Jonatan Lerga, Elena Cuoco.
Sensors 20 (23), 6920 (2020). DOI: 10.3390/s20236920

Parametrized equation of state for neutron star matter with continuous sound speed.
Michael F. O’Boyle, Charalampos Markakis, Nikolaos Stergioulas, Jocelyn S. Read.
Physical Review D 102, 083027 (2020). arXiv:2008.03342. DOI: 10.1103/PhysRevD.102.083027

Neural network reconstruction of the dense matter equation of state derived from the parameters of neutron stars.
Filip Morawski, Michał Bejger.
Astronomy and Astrophysics 642, A78 (2020). arXiv:2006.07194. DOI: 10.1051/0004-6361/202038130

Astrophysical Implications of Neutron Star Inspiral and Coalescence.
John L. Friedman, Nikolaos Stergioulas.
International Journal of Modern Physics D 29, 2041015 (2020). arXiv:2005.14135. DOI: 10.1142/S0218271820410151

Impact of eccentricity on the gravitational wave searches for binary black holes: High mass case.
Antoni Ramos-Buades, Shubhanshu Tiwari, Maria Haney, Sascha Husa.
Physical Review D 102, 043005 (2020). arXiv:2005.14016. DOI: 10.1103/PhysRevD.102.043005

Characterization of systematic error in Advanced LIGO calibration.
Ling Sun et al.
Classical and Quantum Gravity 37, 225008 (2020). arXiv:2005.02531. DOI: 10.1088/1361-6382/abb14e

Equation of state constraints from the threshold binary mass for prompt collapse of neutron star mergers.
Andreas Bauswein, Sebastian Blacker, Vimal Vijayan, Nikolaos Stergioulas, Katerina Chatziioannou, James A. Clark, Niels-Uwe F. Bastian, David B. Blaschke, Mateusz Cierniak, Tobias Fischer.
Physical Review Letters 125, 141103 (2020). arXiv:2004.00846. DOI: 10.1103/PhysRevLett.125.141103

Accelerating the evaluation of inspiral-merger-ringdown waveforms with adapted grids.
Cecilio García-Quirós, Sascha Husa, Maite Mateu-Lucena, Angela Borchers.
Classical and Quantum Gravity 38, (1):015006 (2020). arXiv:2001.10897. DOI:

Seismic array measurements at Virgo’s west end building for the configuration of a Newtonian-noise cancellation system.
M.C. Tringali et al.
Classical and Quantum Gravity 37, 025005 (2020). arXiv:1912.08619. DOI: 10.1088/1361-6382/ab5c43

Convolutional neural network classifier for the output of the time-domain F-statistic all-sky search for continuous gravitational waves.
Filip Morawski, Michał Bejger, Paweł Ciecieląg.
Machine Learning: Science and Technology 1, 025016 (2020). arXiv:1907.06917 DOI: 10.1088/2632-2153/ab86c7

Towards the routine use of subdominant harmonics in gravitational-wave inference: Reanalysis of GW190412 with generation X waveform models.
Marta Colleoni, Maite Mateu-Lucena, Héctor Estellés, Cecilio García-Quirós, David Keitel, Geraint Pratten, Antoni Ramos-Buades, Sascha Husa.
Physical Review D 103, 024029 (2021). arXiv:2010.05830. DOI:

Time-frequency track distance for comparing continuous gravitational wave signals.
Rodrigo Tenorio, David Keitel, Alicia M. Sintes.
Physical Review D 103, 064053 (2021). arXiv:2012.05752. DOI: 10.1103/PhysRevD.103.064053

Searches for Compact Binary Coalescence Events using Neural Networks in LIGO/Virgo Second Observation Period.
Menendez-Vazquez, M. Kolstein, M. Martínez, Ll.M. Mir.
Physical Review D 103, 062004 (2021). arXiv:2012.10702. DOI: 10.1103/PhysRevD.103.062004

Time domain phenomenological model of gravitational wave subdominant harmonics for quasi-circular non-precessing binary black hole coalescences.
Héctor Estellés, Sascha Husa, Marta Colleoni, David Keitel, Maite Mateu-Lucena, Cecilio García-Quirós, Antoni Ramos-Buades, Angela Borchers.
Physical Review D 103, 064053 (2021). arXiv:2012.05752. DOI: 10.1103/PhysRevD.103.064053

Nested sampling with normalizing flows for gravitational-wave inference.
Michael J. Williams, John Veitch, Chris Messenger.
Physical Review D103, 103006 (2021). arXiv: 2102.11056. DOI: 10.1103/PhysRevD.103.103006

The effect of floating-point precision on narrow-band all-sky continuous gravitational-wave search algorithm.
M.F. Nagy-Egri, M. Bejger
Astronomy and Computing 35, 100452 (2021). DOI: 10.1016/j.ascom.2021.100452

PyFstat: a Python package for continuous gravitational-wave data analysis.
David Keitel, Rodrigo Tenorio Gregory Ashton, Reinhard Prix.
Journal of Open Source Software 6 (2021). arXiv: 2101.10915. DOI: 10.21105/joss.03000

Automated source of squeezed vacuum states driven by finite state machine based software.
C. Nguyen, M. Bawaj, V. Sequino, M. Barsuglia, M. Bazzan, E. Calloni, G. Ciani, L. Conti, B. D’Angelo, R. De Rosa, L. Di Fiore, S. Di Pace, V. Fafone, B. Garaventa, A. Gennai, L. Giacoppo, I. Khan, M. Leonardi, E. Majorana, L Naticchioni, F. Paoletti, D. Passuello, M. Pegoraro, F. Ricci, A. Rocchi, M. Vardaro, H. Vocca, J.-P. Zendri, M. De Laurentis, and F. Sorrentino.
Review of Scientific Instruments 92, 054504 (2021). DOI: 10.1063/5.0046317

Systematics of prompt black-hole formation in neutron star mergers.
Andreas Bauswein, Sebastian Blacker, Georgios Lioutas, Theodoros Soultanis, Vimal Vijayan, Nikolaos Stergioulas.
Physical Review D 103, 123004 (2021). arXiv: 2010.0446. DOI: 10.1103/PhysRevD.103.123004

Seismic glitchness at Sos Enattos site: impact on intermediate black hole binaries detection efficiency.
A. Allocca, A. Berbellini, L. Boschi, E. Calloni, G.L. Cardello, A. Cardini, M. Carpinelli, A. Contu, L. D’Onofrio, D. D’Urso, D. Dell’Aquila, R. De Rosa, L. Di Fiore, M. Di Giovanni, S. Di Pace, L. Errico, I. Fiori, C. Giunchi, A. Grado, J. Harms, E. Majorana, V. Mangano, M. Marsella, C. Migoni, L. Naticchoni, M. Olivieri, G. Oggiano, F. Paoletti, M. Punturo, P. Puppo, P. Rapagnani, F. Ricci, D. Rozza, G. Saccorotti, V. Sequino, V. Sipala, I. Tosta E. Melo, L. Trozzo.
The European Physical Journal Plus, 136 (5) (2021). DOI: 10.1140/epjp/s13360-021-01450-8

Computationally efficient models for the dominant and subdominant harmonic modes of precessing binary black holes.
Geraint Pratten, Cecilio García-Quirós, Marta Colleoni, Antoni Ramos-Buades, Héctor Estellés, Maite Mateu-Lucena, Rafel Jaume, Maria Haney, David Keitel, Jonathan E. Thompson, Sascha Husa.
Physical Review D 103, 104056 (2021). arXiv: 2004.06503. DOI: 10.1103/PhysRevD.103.104056

Anomaly detection in gravitational waves data using convolutional autoencoders.
Filip Morawski, Michał Bejger, Elena Cuoco, Luigia Petre.
Machine Learning: Science and Technology 2, 045014 (2021). arXiv: 2103.07688. DOI: 10.1088/2632-2153/abf3d0

Generalised gravitational wave burst generation with generative adversarial networks.
J. McGinn, C. Messenger, M.J. Williams, I.S. Heng.
Classical and Quantum Gravity 38, 155005 (2021). arXiv: 2103.01641. DOI: 101088/1361-6382/ac09cc

Phenomenological time domain model for dominant quadrupole gravitational wave signal of coalescing binary black holes.
Héctor Estellés, Antoni Ramos-Buades, Sasch Husa, Cecilio García-Quirós, Marta Colleoni, Leïla Haegel, Rafel Jaume.
Physical Review D 103, 124060 (2021). arXiv: 2004.08302. DOI: 10.1103/PhysRevD.103.124060

Frequency deviations in universal relations of isolated neutron stars and postmerger remnants.
Georgios Lioutas, Andreas Bauswein, Nikolaos Stergioulas.
Physical Review D 104, 043011 (2021). arXiv: 2102.12455. DOI: 10.1103/PhysRevD.104.043011

Application of a hierarchical MCMC follow-up to Advanced LIGO continuous gravitational-wave candidates.
Rodrigo Tenorio, David Keitel, Alicia M. Sintes.
Physical Review D 104, 084012 (2021). arXiv: 2105.13860. DOI: 10.1103/PhysRevD.104.084012

Multimodal Analysis of Gravitational Wave Signals and Gamma-Ray Bursts from Binary Neutron Star Mergers.
Elena Cuoco, Barbara Patricelli, Alberto Iess, Filip Morawski.
Universe 7 (11), 394 (2021). arXiv: 2110.09833. DOI: 10.3390/universe7110394

INSTANCE – the Italian seismic dataset for machine learning.
Alberto Michelini, Spina Cianetti, Sonja Gaviano, Carlo Giunchi, Dario Jozinović, Valentino Lauciani.
Earth System Science Data 13, 5509–5544 (2021). DOI: 10.5194/essd-13-5509-2021

Search methods for continuous gravitational-wave signals from unknown sources in the advanced-detector era.
Rodrigo Tenorio, David Keitel, Alicia M. Sintes.
Universe 7 (12), 474 (2021). arXiv: 2105.05075. DOI: 10.3390/universe7120474

A Detailed Analysis of GW190521 with Phenomenological Waveform Models.
Héctor Estellés, Sascha Husa, Marta Colleoni, Maite Mateu-Lucena, Maria de Lluc Planas, Cecilio García-Quirós, David Keitel, Antoni Ramos-Buades, Ajit Kumar Mehta, Alessandra Buonanno, Serguei Ossokine.
The Astrophysical Journal 924 (2), 18 (2022). arXiv: 2105.06360.  DOI: 10.3847/1538-4357/ac33a0

Bayesian parameter estimation using conditional variational autoencoders for gravitational-wave astronomy.
Hunter Gabbard, Chris Messenger, Ik Siong Heng, Francesco Tonolini, Roderick Murray-Smith.
Nature Physics 18, 112-117 (2022). DOI: 10.1038/s41567-021-01425-7

Empirical estimating the distribution of the loudest candidate from a gravitational-wave search.
Rodrigo Tenorio, Luana M. Modafferi, David Keitel, Alicia M. Sintes.
Physical Review D 105, 044029 (2022). arXiv: 2111.12032. DOI:

Utilizing Gaussian mixture models in all-sky searches for short-duration gravitational wave bursts.
Dixeena Lopez, V. Gayathri, Archana Pai, Ik Siong Heng, Chris Messenger, Sagar Kumar Gupta.
Physical Review D 105, 063024 (2022). arXiv: 2112.06608. DOI: 10.1103/PhysRevD.105.063024

Transfer learning: improving neural network based prediction of earthquake ground shaking for an area with insufficient training data.
Dario Jozinović, Anthony Lomax, Ivan Štajduhar, Alberto Michelini .
Geophysical Journal International 229, 704–718 (2022). arXiv: 2105.05075. DOI: 10.1093/gji/ggab488

Time-domain phenomenological model of gravitational-wave subdominant harmonics for quasicircular nonprecessing binary black hole coalescences.
Héctor Estellés, Sascha Husa, Marta Colleoni, David Keitel, Maite Mateu-Lucena, Cecilio García-Quirós, Antoni Ramos-Buades, Angela Borchers.
Physcial Review D 105, 084039 (2022). DOI: 10.1103/PhysRevD.105.084039

New twists in compact binary waveform modeling: A fast time-domain model for precession
Héctor Estellés, Marta Colleoni, Cecilio García-Quirós, Sascha Husa, David Keitel, Maite Mateu-Lucena, Maria de Lluc Planas, Antoni Ramos-Buades.
Physical Review D 105, 084040 (2022). arXiv: 2105.05872. DOI: 10.1103/PhysRevD.105.084040

Autoencoder-driven Spiral Representation Learning for Gravitational Wave Surrogate Modelling
Paraskevi Nousi, Styliani-Christina Fragkouli, Nikolaos Passalis, Panagiotis Iosif, Theocharis Apostolatos, George Pappas, Nikolaos Stergioulas, Anastasios Tefas.
Neurocomputing 491, 67–77 (2022). arXiv: 2107.04312. DOI: 10.1016/j.neucom2022.03.052

Rapid parameter estimation for an all-sky continuous gravitational wave search using conditional varitational auto-encoders.
Joe Bayley, Chris Messenger, Graham Woan.
Physical Review D 106, 083022 (2022). arXiv: 2209.02031. DOI: 10.1103/PhysRevD.106.083022

Prospects for detecting and localizing short-duration transient gravitational waves from glitching neutron stars without electromagnetic counterparts.
Dixeena Lopez, Shubhanshu Tiwari, Marco Drago, David Keitel, Claudia Lazzaro, Giovanni Andrea Prodi.
Physical Review D 106, 103037 (2022). arXiv: 2206.15415. DOI: 10.1103/PhysRevD.106.103037

Observational limits on the rate of radiation-driven binary black hole capture events.
Michael Ebersold, Shubhanshu Tiwari, Leigh Smith, Yeong-Bok Bae, Gungwon Kang, Daniel Williams, Achamveedu Gopakumar, Ik Siong Heng, Maria Haney.
Physical Review D 106, 104014 (2022). arXiv: 2208.07762. DOI: 10.1103/PhysRevD.106.104014

Parameter estimation with the current generation of phenomenological waveform models applied to the black hole mergers of GWTC-1.
Maite Mateu-Lucena, Sascha Husa, Marta Colleoni, Héctor Estellés, Cecilio García-Quirós, David Keitel, Maria de Lluc Planas, Antoni Ramos-Buades.
Monthly Notices of the Royal Astronomical Society 517, 2403–2425 (2022). arXiv: 2105.05960. DOI: 10.1093/mnras/stac2724

Detecting dense-matter phase transition signatures in neutron star mass-radius measurements as data anomalies using normalizing flows.
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