Zobrazeno 1 - 10
of 32 026
pro vyhledávání: '"A. Kalyan"'
Autor:
Juhasz, Matyas, Dutia, Kalyan, Franks, Henry, Delahunty, Conor, Mills, Patrick Fawbert, Pim, Harrison
Climate decision making is constrained by the complexity and inaccessibility of key information within lengthy, technical, and multi-lingual documents. Generative AI technologies offer a promising route for improving the accessibility of information
Externí odkaz:
http://arxiv.org/abs/2410.23902
Autor:
Kokolis, Apostolos, Kuchnik, Michael, Hoffman, John, Kumar, Adithya, Malani, Parth, Ma, Faye, DeVito, Zachary, Sengupta, Shubho, Saladi, Kalyan, Wu, Carole-Jean
Reliability is a fundamental challenge in operating large-scale machine learning (ML) infrastructures, particularly as the scale of ML models and training clusters continues to grow. Despite decades of research on infrastructure failures, the impact
Externí odkaz:
http://arxiv.org/abs/2410.21680
Autor:
Portaluri, Elisa, Ragazzoni, Roberto, Greggio, Davide, Arcidiacono, Carmelo, Bergomi, Maria, Di Filippo, Simone, Dima, Marco, Farinato, Jacopo, Machado, Tânia Gomes, Magrin, Demetrio, Santhakumari, Kalyan K. R., Viotto, Valentina
The Ingot WFS belongs to a class of pupil-plane WFSs designed to address the challenges posed by Sodium Laser Guide Stars, and consists of a combination of refractive and reflective surfaces, arranged into a complex prismatic shape that extends in th
Externí odkaz:
http://arxiv.org/abs/2410.06259
Autor:
Machado, Tânia Gomes, Di Filippo, Simone, Santhakumari, Kalyan K. R., Bergomi, Maria, Greggio, Davide, Portaluri, Elisa, Malik, Dheeraj, Nesme, César, Arcidiacono, Carmelo, Ballone, Alessandro, Battaini, Federico, Viotto, Valentina, Ragazzoni, Roberto, Dima, Marco, Marafatto, Luca, Farinato, Jacopo, Magrin, Demetrio, Lessio, Luigi, Umbriaco, Gabriele
The Ingot WFS was designed to overcome some of the challenges present in classical wavefront sensors when they deal with sodium LGSs. This innovative sensor works by sensing the full 3D volume of the elongated LGS and is suitable for use in very larg
Externí odkaz:
http://arxiv.org/abs/2410.06260
This paper deals with bilateral-gamma (BG) approximation to functionals of an isonormal Gaussian process. We use Malliavin-Stein method to obtain the error bounds for the smooth Wasserstein distance. As by-products, the error bounds for variance-gamm
Externí odkaz:
http://arxiv.org/abs/2409.20546
Scent marks play a crucial role in both territorial and sexual communication in many species. We investigated how free-ranging dogs respond to scent marks from individuals of different identities in terms of sex and group, across varying strategic lo
Externí odkaz:
http://arxiv.org/abs/2409.12247
Autor:
Beck, Thomas, Baroni, Alessandro, Bennink, Ryan, Buchs, Gilles, Perez, Eduardo Antonio Coello, Eisenbach, Markus, da Silva, Rafael Ferreira, Meena, Muralikrishnan Gopalakrishnan, Gottiparthi, Kalyan, Groszkowski, Peter, Humble, Travis S., Landfield, Ryan, Maheshwari, Ketan, Oral, Sarp, Sandoval, Michael A., Shehata, Amir, Suh, In-Saeng, Zimmer, Christopher
Quantum Computing (QC) offers significant potential to enhance scientific discovery in fields such as quantum chemistry, optimization, and artificial intelligence. Yet QC faces challenges due to the noisy intermediate-scale quantum era's inherent ext
Externí odkaz:
http://arxiv.org/abs/2408.16159
Autor:
Bhuyan, Kalyan, Gohain, Mrinnoy M.
Non-singular cosmological models, particularly the idea of emergent cosmology have been explored to describe the non-singular origin of the Universe. Recently, zero-point length cosmology has shown some positive insights into some non-singular aspect
Externí odkaz:
http://arxiv.org/abs/2408.14943
In this article, we first obtain, for the Kolmogorov distance, an error bound between a tempered stable and a compound Poisson distribution and also an error bound between a tempered stable and an alpha stable distribution via Stein method. For the s
Externí odkaz:
http://arxiv.org/abs/2408.09487
This project investigates the efficacy of Large Language Models (LLMs) in understanding and extracting scientific knowledge across specific domains and to create a deep learning framework: Knowledge AI. As a part of this framework, we employ pre-trai
Externí odkaz:
http://arxiv.org/abs/2408.04651