Zobrazeno 1 - 10
of 151 214
pro vyhledávání: '"A. Moß"'
Autor:
Ted von Hippel, J. Farihi, J. L. Provencal, S. J. Kleinman, J. E. Pringle, A. Swan, G. Fontaine, J. J. Hermes, J. Sargent, Z. Savery, W. Cooper, V. Kim, V. Kozyreva, M. Krugov, A. Kusakin, A. Moss, W. Ogloza, Erika Pakštienė, A. Serebryanskiy, Eda Sonbas, B. Walter, M. Zejmo, S. Zola
Publikováno v:
The Astrophysical Journal, Vol 963, Iss 2, p 113 (2024)
More than 36 yr have passed since the discovery of the infrared excess from circumstellar dust orbiting the white dwarf G29-38, which at 17.5 pc it is the nearest and brightest of its class. The precise morphology of the orbiting dust remains only ma
Externí odkaz:
https://doaj.org/article/afa53f24a7ee427c8006e4ef350ce5ae
Autor:
A. Moss, P.K. Kaiser
Publikováno v:
Journal of Rock Mechanics and Geotechnical Engineering, Vol 14, Iss 1, Pp 67-81 (2022)
As mines go deeper and get larger, mine designs become more fragile largely due to the response of the rock mass to mining. Ground control and rock support become important levers in the mine construction schedule, production performance, and excavat
Externí odkaz:
https://doaj.org/article/d5ad98db5026409e94d5868c2ce051e9
Autor:
P.K. Kaiser, A. Moss
Publikováno v:
Journal of Rock Mechanics and Geotechnical Engineering, Vol 14, Iss 1, Pp 50-66 (2022)
As mines go deeper, mine designs become more fragile and effective rock support becomes a strategic element for ground control to facilitate timely construction and cost-effective access for uninterrupted production. This article focuses on the desig
Externí odkaz:
https://doaj.org/article/3b35626d945844a58803a18dcdf9ca03
This study explores integrating reinforcement learning (RL) with idealised climate models to address key parameterisation challenges in climate science. Current climate models rely on complex mathematical parameterisations to represent sub-grid scale
Externí odkaz:
http://arxiv.org/abs/2408.16118
Autor:
Caneletti, Matteo, Moss, Ian G
We present a theory of false vacuum decay induced by spherical nucleation seeds. The type of seed considered has a boundary characterised by surface energy terms. The theory applies to false vacuum decay at zero and finite temperatures. Seeded nuclea
Externí odkaz:
http://arxiv.org/abs/2408.12229
Generative models are crucial for applications like data synthesis and augmentation. Diffusion, Flow Matching and Continuous Normalizing Flows have shown effectiveness across various modalities, and rely on Gaussian latent variables for generation. A
Externí odkaz:
http://arxiv.org/abs/2408.08558
Autor:
Yoon, Hyein, Sadler, Elaine M., Mahony, Elizabeth K., Aditya, J. N. H. S., Allison, James R., Glowacki, Marcin, Kerrison, Emily F., Moss, Vanessa A., Su, Renzhi, Weng, Simon, Whiting, Matthew, Wong, O. Ivy, Callingham, Joseph R., Curran, Stephen J., Darling, Jeremy, Edge, Alastair C., Ellison, Sara L., Emig, Kimberly L., Garratt-Smithson, Lilian, German, Gordon, Grasha, Kathryn, Koribalski, Baerbel S., Morganti, Raffaella, Oosterloo, Tom, Péroux, Céline, Pettini, Max, Pimbblet, Kevin A., Zheng, Zheng, Zwaan, Martin, Ball, Lewis, Bock, Douglas C. -J., Brodrick, David, Bunton, John D., Cooray, F. R., Edwards, Philip G., Hayman, Douglas B., Hotan, Aidan W., Lee-Waddell, K., McClure-Griffiths, N. M., Ng, A., Phillips, Chris J., Raja, Wasim, Voronkov, Maxim A., Westmeier, Tobias
The First Large Absorption Survey in HI (FLASH) is a large-area radio survey for neutral hydrogen in the redshift range 0.4
Externí odkaz:
http://arxiv.org/abs/2408.06626
Autor:
Moss, Robert J.
Eliciting harmful behavior from large language models (LLMs) is an important task to ensure the proper alignment and safety of the models. Often when training LLMs, ethical guidelines are followed yet alignment failures may still be uncovered through
Externí odkaz:
http://arxiv.org/abs/2408.08899
Autor:
Moss, David J.
Publikováno v:
Advanced Physics Research Vol. 3 (2024)
Microwave transversal filters, which are implemented based on the transversal filter structure in digital signal processing, offer a high reconfigurability for achieving a variety of signal processing functions without changing hardware. When impleme
Externí odkaz:
http://arxiv.org/abs/2408.03547
We present here RadioSED, a Bayesian inference framework tailored to modelling and classifying broadband radio spectral energy distributions (SEDs) using only data from publicly-released, large-area surveys. We outline the functionality of RadioSED,
Externí odkaz:
http://arxiv.org/abs/2407.16201