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Deep neural networks to enable real-time multimessenger astrophysics

Physical review. D, 2018-02, Vol.97 (4), Article 044039

2018

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Classification and unsupervised clustering of LIGO data with Deep Transfer Learning

Physical review. D, 2018-05, Vol.97 (10), Article 101501

2018

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Characterization of numerical relativity waveforms of eccentric binary black hole mergers

Physical review. D, 2019-08, Vol.100 (4), p.1, Article 044016

2019

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Artificial neural network subgrid models of 2D compressible magnetohydrodynamic turbulence

Physical review. D, 2020-04, Vol.101 (8), Article 084024

2020

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Eccentric, nonspinning, inspiral, Gaussian-process merger approximant for the detection and characterization of eccentric binary black hole mergers

Physical review. D, 2018-01, Vol.97 (2), Article 024031

2018

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Fusing numerical relativity and deep learning to detect higher-order multipole waveforms from eccentric binary black hole mergers

Physical review. D, 2019-08, Vol.100 (4), p.1, Article 044025

2019

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Physics of eccentric binary black hole mergers: A numerical relativity perspective

Physical review. D, 2019-09, Vol.100 (6), Article 064003

2019

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Detection of eccentric supermassive black hole binaries with pulsar timing arrays: Signal-to-noise ratio calculations

Physical review. D, 2015-09, Vol.92 (6), Article 063010

2015

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Probing neutron star structure via f -mode oscillations and damping in dynamical spacetime models

Physical review. D, 2019-04, Vol.99 (8), p.1, Article 084024

2019

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Complete waveform model for compact binaries on eccentric orbits

Physical review. D, 2017-01, Vol.95 (2), Article 024038

2017

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Gravitational Waves from Accreting Neutron Stars Undergoing Common-envelope Inspiral

The Astrophysical journal, 2018-04, Vol.857 (1), p.38

2018

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Proposed search for the detection of gravitational waves from eccentric binary black holes

Physical review. D, 2016-02, Vol.93 (4), Article 043007

2016

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Statistically-informed deep learning for gravitational wave parameter estimation

Machine learning: science and technology, 2022-03, Vol.3 (1), p.15007

2022

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FAIR principles for AI models with a practical application for accelerated high energy diffraction microscopy

Scientific data, 2022-11, Vol.9 (1), p.657-657, Article 657

2022

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Correction: the TEOGIC study project: a comprehensive characterization of early onset gastrointestinal cancer in the Northern area of Spain

BMC cancer, 2024-07, Vol.24 (1), p.1-1, Article 819

2024

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The TEOGIC study project: a comprehensive characterization of early onset gastrointestinal cancer in the Northern area of Spain

BMC cancer, 2024-06, Vol.24 (1), p.668-10, Article 668

2024

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Inference-Optimized AI and High Performance Computing for Gravitational Wave Detection at Scale

Frontiers in artificial intelligence, 2022-02, Vol.5, p.828672-828672

2022

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FAIR for AI: An interdisciplinary and international community building perspective

Scientific data, 2023-07, Vol.10 (1), p.487-487, Article 487

2023

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Magnetohydrodynamics with physics informed neural operators

Machine learning: science and technology, 2023-09, Vol.4 (3), p.35002

2023

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Applications of physics informed neural operators

Machine learning: science and technology, 2023-06, Vol.4 (2), p.25022

2023

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Physics-inspired spatiotemporal-graph AI ensemble for the detection of higher order wave mode signals of spinning binary black hole mergers

Machine learning: science and technology, 2024-06, Vol.5 (2), p.25056

2024

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A FAIR and AI-ready Higgs boson decay dataset

Scientific data, 2022-02, Vol.9 (1), p.31-31, Article 31

2022

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Effect of cadmium on the concentration of essential metals in a human chondrocyte micromass culture

Journal of trace elements in medicine and biology, 2020-12, Vol.62, p.126614, Article 126614

2020

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Convergence of artificial intelligence and high performance computing on NSF-supported cyberinfrastructure

Journal of big data, 2020-10, Vol.7 (1), p.1-12, Article 88

2020

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End-to-end AI framework for interpretable prediction of molecular and crystal properties

Machine learning: science and technology, 2023-06, Vol.4 (2), p.25036

2023

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Deep neural networks to enable real-time multimessenger astrophysics

Classification and unsupervised clustering of LIGO data with Deep Transfer Learning

Characterization of numerical relativity waveforms of eccentric binary black hole mergers

Artificial neural network subgrid models of 2D compressible magnetohydrodynamic turbulence

Eccentric, nonspinning, inspiral, Gaussian-process merger approximant for the detection and characterization of eccentric binary black hole mergers

Fusing numerical relativity and deep learning to detect higher-order multipole waveforms from eccentric binary black hole mergers

Physics of eccentric binary black hole mergers: A numerical relativity perspective

Detection of eccentric supermassive black hole binaries with pulsar timing arrays: Signal-to-noise ratio calculations

Probing neutron star structure via f -mode oscillations and damping in dynamical spacetime models

Complete waveform model for compact binaries on eccentric orbits

Gravitational Waves from Accreting Neutron Stars Undergoing Common-envelope Inspiral

Proposed search for the detection of gravitational waves from eccentric binary black holes

Statistically-informed deep learning for gravitational wave parameter estimation

FAIR principles for AI models with a practical application for accelerated high energy diffraction microscopy

Correction: the TEOGIC study project: a comprehensive characterization of early onset gastrointestinal cancer in the Northern area of Spain

The TEOGIC study project: a comprehensive characterization of early onset gastrointestinal cancer in the Northern area of Spain

Inference-Optimized AI and High Performance Computing for Gravitational Wave Detection at Scale

FAIR for AI: An interdisciplinary and international community building perspective

Magnetohydrodynamics with physics informed neural operators

Applications of physics informed neural operators

Physics-inspired spatiotemporal-graph AI ensemble for the detection of higher order wave mode signals of spinning binary black hole mergers

A FAIR and AI-ready Higgs boson decay dataset

Effect of cadmium on the concentration of essential metals in a human chondrocyte micromass culture

Convergence of artificial intelligence and high performance computing on NSF-supported cyberinfrastructure

End-to-end AI framework for interpretable prediction of molecular and crystal properties

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