Zobrazeno 1 - 10
of 6 910
pro vyhledávání: '"Rafiei P"'
Autor:
Sand, Ketan R., Curtin, Alice P., Michilli, Daniele, Kaspi, Victoria M., Fonseca, Emmanuel, Nimmo, Kenzie, Pleunis, Ziggy, Shin, Kaitlyn, Bhardwaj, Mohit, Brar, Charanjot, Dobbs, Matt, Eadie, Gwendolyn, Gaensler, B. M., Joseph, Ronniy C., Leung, Calvin, Main, Robert, Masui, Kiyoshi W., Mckinven, Ryan, Pandhi, Ayush, Pearlman, Aaron B., Rafiei-Ravandi, Masoud, Sammons, Mawson W., Smith, Kendrick, Stairs, Ingrid H.
We present a spectro-temporal analysis of 137 fast radio bursts (FRBs) from the first CHIME/FRB baseband catalog, including 125 one-off bursts and 12 repeat bursts, down to microsecond resolution using the least-squares optimization fitting routine:
Externí odkaz:
http://arxiv.org/abs/2408.13215
Autor:
Cook, Amanda M., Scholz, Paul, Pearlman, Aaron B., Abbott, Thomas C., Cruces, Marilyn, Gaensler, B. M., Fengqiu, Dong, Michilli, Daniele, Eadie, Gwendolyn, Kaspi, Victoria M., Stairs, Ingrid, Tan, Chia Min, Bhardwaj, Mohit, Cassanelli, Tomas, Curtin, Alice P., Ibik, Adaeze L., Lazda, Mattias, Masui, Kiyoshi W., Pandhi, Ayush, Rafiei-Ravandi, Masoud, Sammons, Mawson W., Shin, Kaitlyn, Smith, Kendrick, Stenning, David C.
We present an extensive contemporaneous X-ray and radio campaign performed on the repeating fast radio burst (FRB) source FRB 20220912A for eight weeks immediately following the source's detection by CHIME/FRB. This includes X-ray data from XMM-Newto
Externí odkaz:
http://arxiv.org/abs/2408.11895
Autor:
Rafiei, A., Haghighat, M.
We consider the electromagnetic form factors ratio in the Rosenbluth and polarization methods. We explore the impact of adding new particles as the mediators in the electron-proton scattering on these ratios. Consequently, we find some bound on the s
Externí odkaz:
http://arxiv.org/abs/2408.01165
Autor:
Nahid, Md Mahadi Hasan, Rafiei, Davood
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities in parsing textual data and generating code. However, their performance in tasks involving tabular data, especially those requiring symbolic reasoning, faces chal
Externí odkaz:
http://arxiv.org/abs/2406.17961
Autor:
Rafiei, Seide Saba, Chevalier, Samuel
DC Optimal Power Flow (DCOPF) is a key operational tool for power system operators, and it is embedded as a subproblem in many challenging optimization problems (e.g., line switching). However, traditional CPU-based solve routines (e.g., simplex) hav
Externí odkaz:
http://arxiv.org/abs/2406.13191
Autor:
Nimmo, Kenzie, Pleunis, Ziggy, Beniamini, Paz, Kumar, Pawan, Lanman, Adam E., Li, D. Z., Main, Robert, Sammons, Mawson W., Andrew, Shion, Bhardwaj, Mohit, Chatterjee, Shami, Curtin, Alice P., Fonseca, Emmanuel, Gaensler, B. M., Joseph, Ronniy C., Kader, Zarif, Kaspi, Victoria M., Lazda, Mattias, Leung, Calvin, Masui, Kiyoshi W., Mckinven, Ryan, Michilli, Daniele, Pandhi, Ayush, Pearlman, Aaron B., Rafiei-Ravandi, Masoud, Sand, Ketan R., Shin, Kaitlyn, Smith, Kendrick, Stairs, Ingrid H.
Fast radio bursts (FRBs) are micro-to-millisecond duration radio transients that originate mostly from extragalactic distances. The emission mechanism responsible for these high luminosity, short duration transients remains debated. The models are br
Externí odkaz:
http://arxiv.org/abs/2406.11053
Meta-learning involves multiple learners, each dedicated to specific tasks, collaborating in a data-constrained setting. In current meta-learning methods, task learners locally learn models from sensitive data, termed support sets. These task learner
Externí odkaz:
http://arxiv.org/abs/2406.00249
Extracted event data from information systems often contain a variety of process executions making the data complex and difficult to comprehend. Unlike current research which only identifies the variability over time, we focus on other dimensions tha
Externí odkaz:
http://arxiv.org/abs/2406.04347
Autor:
Nahid, Md Mahadi Hasan, Rafiei, Davood
Table reasoning is a challenging task that requires understanding both natural language questions and structured tabular data. Large language models (LLMs) have shown impressive capabilities in natural language understanding and generation, but they
Externí odkaz:
http://arxiv.org/abs/2404.10150
Publikováno v:
IEEE Transactions on Dependable and Secure Computing (2024), pp. 1-17
Machine learning models are vulnerable to maliciously crafted Adversarial Examples (AEs). Training a machine learning model with AEs improves its robustness and stability against adversarial attacks. It is essential to develop models that produce hig
Externí odkaz:
http://arxiv.org/abs/2403.11833