Zobrazeno 1 - 10
of 10 029
pro vyhledávání: '"A. Mozaffari"'
Publikováno v:
Geoscientific Model Development, Vol 16, Pp 2737-2752 (2023)
The prediction of precipitation patterns up to 2 h ahead, also known as precipitation nowcasting, at high spatiotemporal resolutions is of great relevance in weather-dependent decision-making and early warning systems. In this study, we are aiming to
Externí odkaz:
https://doaj.org/article/f6c04728777d4034aab9b9d3600fe548
Publikováno v:
Geoscientific Model Development, Vol 15, Pp 8931-8956 (2022)
Numerical weather prediction (NWP) models solve a system of partial differential equations based on physical laws to forecast the future state of the atmosphere. These models are deployed operationally, but they are computationally very expensive. Re
Externí odkaz:
https://doaj.org/article/607a06ca4ff94c2186d8712016b38127
Autor:
Ortiz, Brenden R., Meier, William R., Pokharel, Ganesh, Chamorro, Juan, Yang, Fazhi, Mozaffari, Shirin, Thaler, Alex, Alvarado, Steven J. Gomez, Zhang, Heda, Parker, David S., Samolyuk, German D., Paddison, Joseph A. M., Yan, Jiaqiang, Ye, Feng, Sarker, Suchismita, Wilson, Stephen D., Miao, Hu, Mandrus, David, McGuire, Michael A.
The kagome motif is a versatile platform for condensed matter physics, hosting rich interactions between magnetic, electronic, and structural degrees of freedom. In recent years, the discovery of a charge density wave (CDW) in the AV$_3$Sb$_5$ superc
Externí odkaz:
http://arxiv.org/abs/2411.10635
Autor:
Rajabalifardi, Kamyar, Bhattacharya, Sagnik, Afshang, Mehrnaz, Mozaffari, Mohammad, Cioffi, John M.
This paper introduces a novel power allocation and subcarrier optimization algorithm tailored for fixed wireless access (FWA) networks operating under low-rank channel conditions, where the number of subscriber antennas far exceeds those at the base
Externí odkaz:
http://arxiv.org/abs/2410.21786
Large Language Models (LLMs) have revolutionized natural language understanding and generation tasks but suffer from high memory consumption and slow inference times due to their large parameter sizes. Traditional model compression techniques, such a
Externí odkaz:
http://arxiv.org/abs/2410.09615
Autor:
Mudiyanselage, Nivarthana W. Y. A. Y., DeTellem, Derick, Chanda, Amit, Duong, Anh Tuan, Hsieh, Tzung-En, Frisch, Johannes, Bär, Marcus, Madhogaria, Richa Pokharel, Mozaffari, Shirin, Arachchige, Hasitha Suriya, Mandrus, David, Srikanth, Hariharan, Witanachchi, Sarath, Phan, Manh-Huong
The study of magnetoresistance (MR) phenomena has been pivotal in advancing magnetic sensors and spintronic devices. Helimagnets present an intriguing avenue for spintronics research. Theoretical predictions suggest that MR magnitude in the helimagne
Externí odkaz:
http://arxiv.org/abs/2409.19519
Autor:
Zheng, Guoxin, Zhu, Yuan, Mozaffari, Shirin, Mao, Ning, Chen, Kuan-Wen, Jenkins, Kaila, Zhang, Dechen, Chan, Aaron, Arachchige, Hasitha W. Suriya, Madhogaria, Richa P., Cothrine, Matthew, Meier, William R., Zhang, Yang, Mandrus, David, Li, Lu
Publikováno v:
Journal of Physics: Condensed Matter 36, 215501 (2024)
Metals with kagome lattice provide bulk materials to host both the flat-band and Dirac electronic dispersions. A new family of kagome metals is recently discovered in AV6Sn6. The Dirac electronic structures of this material need more experimental evi
Externí odkaz:
http://arxiv.org/abs/2409.05634
Autor:
Attafi, Omar Abdelghani, Clementel, Damiano, Kyritsis, Konstantinos, Capriotti, Emidio, Farrell, Gavin, Fragkouli, Styliani-Christina, Castro, Leyla Jael, Hatos, András, Lenaerts, Tom, Mazurenko, Stanislav, Mozaffari, Soroush, Pradelli, Franco, Ruch, Patrick, Savojardo, Castrense, Turina, Paola, Zambelli, Federico, Piovesan, Damiano, Monzon, Alexander Miguel, Psomopoulos, Fotis, Tosatto, Silvio C. E.
Supervised machine learning (ML) is used extensively in biology and deserves closer scrutiny. The DOME recommendations aim to enhance the validation and reproducibility of ML research by establishing standards for key aspects such as data handling an
Externí odkaz:
http://arxiv.org/abs/2408.07721
Autor:
Mozaffari, Hamid, Marathe, Virendra J.
Membership Inference Attacks (MIAs) determine whether a specific data point was included in the training set of a target model. In this paper, we introduce the Semantic Membership Inference Attack (SMIA), a novel approach that enhances MIA performanc
Externí odkaz:
http://arxiv.org/abs/2406.10218
We propose SLoPe, a Double-Pruned Sparse Plus Lazy Low-rank Adapter Pretraining method for LLMs that improves the accuracy of sparse LLMs while accelerating their pretraining and inference and reducing their memory footprint. Sparse pretraining of LL
Externí odkaz:
http://arxiv.org/abs/2405.16325