Zobrazeno 1 - 10
of 21 651
pro vyhledávání: '"A. Cal"'
Autor:
Bundele, Valay, Çal, Oğuz Ata, Kargi, Bora, Sarıtaş, Karahan, Tezören, Kıvanç, Ghaderi, Zohreh, Lensch, Hendrik
Self-supervised learning (SSL) has emerged as a promising paradigm in medical imaging, addressing the chronic challenge of limited labeled data in healthcare settings. While SSL has shown impressive results, existing studies in the medical domain are
Externí odkaz:
http://arxiv.org/abs/2412.19124
Measurements of Higgs boson processes by the ATLAS and CMS experiments at the LHC use Simplified Template Cross Sections (STXS) as a common framework for the combination of measurements in different decay channels and their further interpretation, e.
Externí odkaz:
http://arxiv.org/abs/2408.13301
Autor:
A. Cal, G. Tiscornia
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-3-W12-2020, Pp 171-176 (2020)
This paper presents a new methodology for mapping summer crops in Uruguay, during the season, based on time-series analysis of the EVI vegetation index derived from the MODIS sensor. Time-series were processed with the k-means unsupervised machine le
Externí odkaz:
https://doaj.org/article/105c9cf20c56494fa35877ef8e19d3d0
We study space-time resolved densities of particle-hole pairs produced by an external time-dependent field acting on non-interacting non-relativistic particles. It is shown that, at least in some cases, the densities are not affected by Fermi-Dirac o
Externí odkaz:
http://arxiv.org/abs/2407.13905
We investigate relativistic wavepacket dynamics for an electron tunneling through a potential barrier employing space-time resolved solutions to relativistic quantum field theory (QFT) equations. We prove by linking the QFT property of micro-causalit
Externí odkaz:
http://arxiv.org/abs/2407.07160
Autor:
Meng, Zhong, Wu, Zelin, Prabhavalkar, Rohit, Peyser, Cal, Wang, Weiran, Chen, Nanxin, Sainath, Tara N., Ramabhadran, Bhuvana
Publikováno v:
Interspeech 2024, Kos Island, Greece
Neural contextual biasing effectively improves automatic speech recognition (ASR) for crucial phrases within a speaker's context, particularly those that are infrequent in the training data. This work proposes contextual text injection (CTI) to enhan
Externí odkaz:
http://arxiv.org/abs/2406.02921
The stable boundary layer (SBL) subjected to large-scale subsidence is studied through large-eddy simulations (LESs) with fixed surface temperature and a linear subsidence velocity profile. These boundary layers reach a truly steady state, where ther
Externí odkaz:
http://arxiv.org/abs/2406.01751
Autor:
Li, Dengchun, Ma, Yingzi, Wang, Naizheng, Ye, Zhengmao, Cheng, Zhiyuan, Tang, Yinghao, Zhang, Yan, Duan, Lei, Zuo, Jie, Yang, Cal, Tang, Mingjie
Fine-tuning Large Language Models (LLMs) is a common practice to adapt pre-trained models for specific applications. While methods like LoRA have effectively addressed GPU memory constraints during fine-tuning, their performance often falls short, es
Externí odkaz:
http://arxiv.org/abs/2404.15159
The stochastic simulation algorithm (SSA) and the corresponding Monte Carlo (MC) method are among the most common approaches for studying stochastic processes. They rely on knowledge of interevent probability density functions (PDFs) and on informati
Externí odkaz:
http://arxiv.org/abs/2402.06536
Autor:
Ayala, Manuel, Sadek, Zein, Ferčák, Ondřej, Cal, Raúl Bayoán, Gayme, Dennice, Meneveau, Charles
Numerical prediction of the interactions between wind and ocean waves is essential for climate modeling and a wide range of offshore operations. Large Eddy Simulation (LES) of the marine atmospheric boundary layer is a practical numerical predictive
Externí odkaz:
http://arxiv.org/abs/2401.12188