Zobrazeno 1 - 10
of 5 946
pro vyhledávání: '"Edwards, A. D."'
Autor:
Helfer, Thomas, Edwards, Thomas D. P., Dafflon, Jessica, Wong, Kaze W. K., Olson, Matthew Lyle
Generating high-resolution simulations is key for advancing our understanding of one of the universe's most violent events: Black Hole mergers. However, generating Black Hole simulations is limited by prohibitive computational costs and scalability i
Externí odkaz:
http://arxiv.org/abs/2411.02453
Scaling laws for large language models (LLMs) have provided useful guidance on how to train ever larger models for predictable performance gains. Time series forecasting shares a similar sequential structure to language, and is amenable to large-scal
Externí odkaz:
http://arxiv.org/abs/2405.13867
We present a framework for the efficient computation of optimal Bayesian decisions under intractable likelihoods, by learning a surrogate model for the expected utility (or its distribution) as a function of the action and data spaces. We leverage re
Externí odkaz:
http://arxiv.org/abs/2311.05742
Autor:
Robinson, Brandon, Bisaillon, Philippe, Edwards, Jodi D., Kendzerska, Tetyana, Khalil, Mohammad, Poirel, Dominique, Sarkar, Abhijit
We consider state and parameter estimation for compartmental models having both time-varying and time-invariant parameters. Though the described Bayesian computational framework is general, we look at a specific application to the susceptible-infecti
Externí odkaz:
http://arxiv.org/abs/2310.16169
Ranked data is commonly used in research across many fields of study including medicine, biology, psychology, and economics. One common statistic used for analyzing ranked data is Kendall's {\tau} coefficient, a non-parametric measure of rank correla
Externí odkaz:
http://arxiv.org/abs/2308.08466
We investigate the possibility of improving the accuracy of the phenomenological waveform model, IMRPhenomD, by jointly optimizing all the calibration coefficients at once, given a set of numerical relativity (NR) waveforms. When IMRPhenomD was first
Externí odkaz:
http://arxiv.org/abs/2306.17245
Autor:
Chia, Horng Sheng, Edwards, Thomas D. P., Wadekar, Digvijay, Zimmerman, Aaron, Olsen, Seth, Roulet, Javier, Venumadhav, Tejaswi, Zackay, Barak, Zaldarriaga, Matias
We report results on the first matched-filtering search for binaries with compact objects having large tidal deformabilities in the LIGO-Virgo gravitational wave (GW) data. The tidal deformability of a body is quantified by the ``Love number" $\Lambd
Externí odkaz:
http://arxiv.org/abs/2306.00050
We present a lightweight, flexible, and high-performance framework for inferring the properties of gravitational-wave events. By combining likelihood heterodyning, automatically-differentiable and accelerator-compatible waveforms, and gradient-based
Externí odkaz:
http://arxiv.org/abs/2302.05333
Autor:
Edwards, Thomas D. P., Wong, Kaze W. K., Lam, Kelvin K. H., Coogan, Adam, Foreman-Mackey, Daniel, Isi, Maximiliano, Zimmerman, Aaron
We propose the use of automatic differentiation through the programming framework jax for accelerating a variety of analysis tasks throughout gravitational wave (GW) science. Firstly, we demonstrate that complete waveforms which cover the inspiral, m
Externí odkaz:
http://arxiv.org/abs/2302.05329
Autor:
Repp, Matthew L.1 (AUTHOR), Edwards, Mark D.2 (AUTHOR), Burch, Christopher S.3 (AUTHOR), Rao, Amith4 (AUTHOR), Chinyere, Ikeotunye Royal4,5 (AUTHOR) ichinyere@arizona.edu
Publikováno v:
Hearts. Sep2024, Vol. 5 Issue 3, p375-388. 14p.
