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Interpretable AI forecasting for numerical relativity waveforms of quasi-circular, spinning, non-precessing binary black hole mergers

13 October 2021

Asad Khan

Eliu A. Huerta

Huihuo Zheng

ArXiv (abs)PDF HTML Github

Papers citing "Interpretable AI forecasting for numerical relativity waveforms of quasi-circular, spinning, non-precessing binary black hole mergers"

6 / 6 papers shown

NeoSySPArtaN: A Neuro-Symbolic Spin Prediction Architecture for higher-order multipole waveforms from eccentric Binary Black Hole mergers using Numerical Relativity

A. Vibho

A. A. Bataineh

137

20 Jul 2023

FAIR AI Models in High Energy Physics

Javier Mauricio Duarte

...

403

09 Dec 2022

Applications of physics informed neural operators

354

23 Mar 2022

Inference-optimized AI and high performance computing for gravitational wave detection at scaleFrontiers in Artificial Intelligence (FAI), 2022

336

26 Jan 2022

AI and extreme scale computing to learn and infer the physics of higher order gravitational wave modes of quasi-circular, spinning, non-precessing binary black hole mergers

Asad Khan

E. A. H. abd

Prayush Kumar

277

13 Dec 2021

Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and BeyondKnowledge and Information Systems (KAIS), 2021

Haoyi Xiong

Jiang Bian

371

476

19 Mar 2021