Zobrazeno 1 - 10
of 86 703
pro vyhledávání: '"A, Mathews"'
This work explores the challenge of enhancing Automatic Speech Recognition (ASR) model performance across various user-specific domains while preserving user data privacy. We employ federated learning and parameter-efficient domain adaptation methods
Externí odkaz:
http://arxiv.org/abs/2408.11873
Autor:
Mathews, D. G., Acharya, H., Crawford, C. B., Gervais, M. H., Jezghani, A. P., McCrea, M., Nelsen, A., Atencio, A., Birge, N., Broussard, L. J., Choi, J. H., Gonzalez, F. M., Li, H., Macsai, N., Mendelsohn, A., Mammei, R. R., Riley, G. V., Whitehead, R. A.
The Nab experiment will measure the electron-neutrino correlation and Fierz interference term in free neutron beta decay to test the Standard Model and probe Beyond the Standard Model Physics. Using National Instrument's PXIe-5171 Reconfigurable Osci
Externí odkaz:
http://arxiv.org/abs/2407.17606
Diffusion models (DPMs) have demonstrated remarkable performance in image generation, often times outperforming other generative models. Since their introduction, the powerful noise-to-image denoising pipeline has been extended to various discriminat
Externí odkaz:
http://arxiv.org/abs/2407.12952
Autor:
Genenz, Ulrike, Anne, Neelanjana, Kılıç, Zeynep, Mathews, Daniel, Ok, Oya, Schmidt, Adrian, Seskir, Zeki Can
This paper examines the intersection of goals and values within grassroots organizations operating in the realm of quantum technologies (QT) education. It delineates a fundamental distinction between the objective to provide education and the drive t
Externí odkaz:
http://arxiv.org/abs/2406.18761
Autor:
Bugiani, Letizia, Belli, Sirio, Park, Minjung, Davies, Rebecca L., Mendel, J. Trevor, Johnson, Benjamin D., Khoram, Amir H., Benton, Chloë, Cimatti, Andrea, Conroy, Charlie, Emami, Razieh, Leja, Joel, Li, Yijia, Maheson, Gabriel, Mathews, Elijah P., Naidu, Rohan P., Nelson, Erica J., Tacchella, Sandro, Terrazas, Bryan A., Weinberger, Rainer
We analyze ionized gas emission lines in deep rest-frame optical spectra of 16 quiescent galaxies at redshift $1.7
Externí odkaz:
http://arxiv.org/abs/2406.08547
We present the first comparison of waveforms evaluated using the effective-one-body (EOB) approach and gravitational self-force (GSF) theory for inspiralling black hole binaries with a non-spinning primary and a spinning secondary. This paper belongs
Externí odkaz:
http://arxiv.org/abs/2406.04108
The nucleation of gas hydrates is of great interest in flow assurance, global energy demand, and carbon capture and storage. A complex molecular understanding is critical to control hydrate nucleation and growth in the context of potential applicatio
Externí odkaz:
http://arxiv.org/abs/2405.05454
Autor:
Park, Minjung, Belli, Sirio, Conroy, Charlie, Johnson, Benjamin D., Davies, Rebecca L., Leja, Joel, Tacchella, Sandro, Mendel, J. Trevor, Benton, Chloë, Bugiani, Letizia, Emami, Razieh, Khoram, Amirhossein, Li, Yijia, Maheson, Gabriel, Mathews, Elijah P., Naidu, Rohan P., Nelson, Erica J., Terrazas, Bryan A., Weinberger, Rainer
Massive quiescent galaxies in the young universe are expected to be quenched rapidly, but it is unclear whether they all experience starbursts before quenching and what physical mechanism drives rapid quenching. We study 16 massive quiescent galaxies
Externí odkaz:
http://arxiv.org/abs/2404.17945
Deep learning (DL) has recently emerged as a pivotal technology for enhancing magnetic resonance imaging (MRI), a critical tool in diagnostic radiology. This review paper provides a comprehensive overview of recent advances in DL for MRI reconstructi
Externí odkaz:
http://arxiv.org/abs/2404.15692
Autor:
Hard, Andrew, Girgis, Antonious M., Amid, Ehsan, Augenstein, Sean, McConnaughey, Lara, Mathews, Rajiv, Anil, Rohan
How well do existing federated learning algorithms learn from client devices that return model updates with a significant time delay? Is it even possible to learn effectively from clients that report back minutes, hours, or days after being scheduled
Externí odkaz:
http://arxiv.org/abs/2403.09086