Zobrazeno 1 - 10
of 62 963
pro vyhledávání: '"Alam, P."'
Next generations of radio surveys are expected to identify tens of millions of new sources, and identifying and classifying their morphologies will require novel and more efficient methods. Self-Organising Maps (SOMs), a type of unsupervised machine
Externí odkaz:
http://arxiv.org/abs/2412.10183
Autor:
Alam, Nahid, Kanjula, Karthik Reddy, Guthikonda, Surya, Chung, Timothy, Vegesna, Bala Krishna S, Das, Abhipsha, Susevski, Anthony, Chan, Ryan Sze-Yin, Uddin, S M Iftekhar, Islam, Shayekh Bin, Santhosh, Roshan, A, Snegha, Sharma, Drishti, Liu, Chen, Chaturvedi, Isha, Winata, Genta Indra, S, Ashvanth., Mukherjee, Snehanshu, Aji, Alham Fikri
The rapid development of large Vision-Language Models (VLMs) has led to impressive results on academic benchmarks, primarily in widely spoken languages. However, significant gaps remain in the ability of current VLMs to handle low-resource languages
Externí odkaz:
http://arxiv.org/abs/2412.07112
Hypergraph is a data structure that enables us to model higher-order associations among data entities. Conventional graph-structured data can represent pairwise relationships only, whereas hypergraph enables us to associate any number of entities, wh
Externí odkaz:
http://arxiv.org/abs/2412.05641
New physics beyond the Standard Model (SM) may appear in the form of non-standard neutrino interactions (NSI). We have studied neutral current (anti)neutrino-nucleon scattering in presence of NSI. We obtain that in this scenario, nucleon matrix eleme
Externí odkaz:
http://arxiv.org/abs/2412.04818
Autor:
Haque, Mahfuzul, Miah, Abu Saleh Musa, Gupta, Debashish, Prince, Md. Maruf Al Hossain, Alam, Tanzina, Sharmin, Nusrat, Ali, Mohammed Sowket, Shin, Jungpil
Heart disease is a leading cause of premature death worldwide, particularly among middle-aged and older adults, with men experiencing a higher prevalence. According to the World Health Organization (WHO), non-communicable diseases, including heart di
Externí odkaz:
http://arxiv.org/abs/2412.04792
Real-time monitoring of critical parameters is essential for energy systems' safe and efficient operation. However, traditional sensors often fail and degrade in harsh environments where physical sensors cannot be placed (inaccessible locations). In
Externí odkaz:
http://arxiv.org/abs/2412.00107
Autor:
Mankali, Lakshmi Likhitha, Bhandari, Jitendra, Alam, Manaar, Karri, Ramesh, Maniatakos, Michail, Sinanoglu, Ozgur, Knechtel, Johann
Large language models (LLMs) have demonstrated remarkable potential with code generation/completion tasks for hardware design. In fact, LLM-based hardware description language (HDL) code generation has enabled the industry to realize complex designs
Externí odkaz:
http://arxiv.org/abs/2411.17569
Using the charge density from the two-parameter Fermi model, a robust and nontrival correlation between binding energis and charge radii of mirror nuclei is newly proposed. This correlation enables simple yet reliable predictions of the nuclear mass
Externí odkaz:
http://arxiv.org/abs/2411.16214
Overfitting remains a significant challenge in deep learning, often arising from data outliers, noise, and limited training data. To address this, we propose Divide2Conquer (D2C), a novel technique to mitigate overfitting. D2C partitions the training
Externí odkaz:
http://arxiv.org/abs/2411.15876
Autor:
DESI Collaboration, Adame, A. G., Aguilar, J., Ahlen, S., Alam, S., Alexander, D. M., Prieto, C. Allende, Alvarez, M., Alves, O., Anand, A., Andrade, U., Armengaud, E., Avila, S., Aviles, A., Awan, H., Bahr-Kalus, B., Bailey, S., Baltay, C., Bault, A., Behera, J., BenZvi, S., Beutler, F., Bianchi, D., Blake, C., Blum, R., Bonici, M., Brieden, S., Brodzeller, A., Brooks, D., Buckley-Geer, E., Burtin, E., Calderon, R., Canning, R., Rosell, A. Carnero, Cereskaite, R., Cervantes-Cota, J. L., Chabanier, S., Chaussidon, E., Chaves-Montero, J., Chebat, D., Chen, S., Chen, X., Claybaugh, T., Cole, S., Cuceu, A., Davis, T. M., Dawson, K., de la Macorra, A., de Mattia, A., Deiosso, N., Dey, A., Dey, B., Ding, Z., Doel, P., Edelstein, J., Eftekharzadeh, S., Eisenstein, D. J., Elbers, W., Elliott, A., Fagrelius, P., Fanning, K., Ferraro, S., Ereza, J., Findlay, N., Flaugher, B., Font-Ribera, A., Forero-Sánchez, D., Forero-Romero, J. E., Frenk, C. S., Garcia-Quintero, C., Garrison, L. H., Gaztañaga, E., Gil-Marín, H., Gontcho, S. Gontcho A, Gonzalez-Morales, A. X., Gonzalez-Perez, V., Gordon, C., Green, D., Gruen, D., Gsponer, R., Gutierrez, G., Guy, J., Hadzhiyska, B., Hahn, C., Hanif, M. M. S, Herrera-Alcantar, H. K., Honscheid, K., Howlett, C., Huterer, D., Iršič, V., Ishak, M., Joyce, R., Juneau, S., Karaçaylı, N. G., Kehoe, R., Kent, S., Kirkby, D., Kong, H., Koposov, S. E., Kremin, A., Krolewski, A., Lahav, O., Lai, Y., Lan, T. -W., Landriau, M., Lang, D., Lasker, J., Goff, J. M. Le, Guillou, L. Le, Leauthaud, A., Levi, M. E., Li, T. S., Lodha, K., Magneville, C., Manera, M., Margala, D., Martini, P., Matthewson, W., Maus, M., McDonald, P., Medina-Varela, L., Meisner, A., Mena-Fernández, J., Miquel, R., Moon, J., Moore, S., Moustakas, J., Mudur, N., Mueller, E., Muñoz-Gutiérrez, A., Myers, A. D., Nadathur, S., Napolitano, L., Neveux, R., Newman, J. A., Nguyen, N. M., Nie, J., Niz, G., Noriega, H. E., Padmanabhan, N., Paillas, E., Palanque-Delabrouille, N., Pan, J., Penmetsa, S., Percival, W. J., Pieri, M. M., Pinon, M., Poppett, C., Porredon, A., Prada, F., Pérez-Fernández, A., Pérez-Ràfols, I., Rabinowitz, D., Raichoor, A., Ramírez-Pérez, C., Ramirez-Solano, S., Rashkovetskyi, M., Ravoux, C., Rezaie, M., Rich, J., Rocher, A., Rockosi, C., Roe, N. A., Rosado-Marin, A., Ross, A. J., Rossi, G., Ruggeri, R., Ruhlmann-Kleider, V., Samushia, L., Sanchez, E., Saulder, C., Schlafly, E. F., Schlegel, D., Schubnell, M., Seo, H., Shafieloo, A., Sharples, R., Silber, J., Slosar, A., Smith, A., Sprayberry, D., Tan, T., Tarlé, G., Taylor, P., Trusov, S., Vaisakh, R., Valcin, D., Valdes, F., Valogiannis, G., Vargas-Magaña, M., Verde, L., Walther, M., Wang, B., Wang, M. S., Weaver, B. A., Weaverdyck, N., Wechsler, R. H., Weinberg, D. H., White, M., Wilson, M. J., Yi, L., Yu, J., Yu, Y., Yuan, S., Yèche, C., Zaborowski, E. A., Zarrouk, P., Zhang, H., Zhao, C., Zhao, R., Zhou, R., Zhuang, T., Zou, H.
We present cosmological results from the measurement of clustering of galaxy, quasar and Lyman-$\alpha$ forest tracers from the first year of observations with the Dark Energy Spectroscopic Instrument (DESI Data Release 1). We adopt the full-shape (F
Externí odkaz:
http://arxiv.org/abs/2411.12022