Zobrazeno 1 - 10
of 62
pro vyhledávání: '"Moghaddam, Mahdi"'
Autor:
Chen, Meng, Arthur, Philip, Feng, Qianyu, Hoang, Cong Duy Vu, Hong, Yu-Heng, Moghaddam, Mahdi Kazemi, Nezami, Omid, Nguyen, Thien, Tangari, Gioacchino, Vu, Duy, Vu, Thanh, Johnson, Mark, Kenthapadi, Krishnaram, Dharmasiri, Don, Duong, Long, Li, Yuan-Fang
Large language models (LLMs) have shown impressive performance in \emph{code} understanding and generation, making coding tasks a key focus for researchers due to their practical applications and value as a testbed for LLM evaluation. Data synthesis
Externí odkaz:
http://arxiv.org/abs/2411.00005
This paper introduces an efficient tensor-vector product technique for the rapid and accurate approximation of integral operators within physics-informed deep learning frameworks. Our approach leverages neural network architectures to evaluate proble
Externí odkaz:
http://arxiv.org/abs/2409.01899
Autor:
Moghaddam, Mahdi, Dzemidzic, Mario, Guerrero, Daniel, Liu, Mintao, Alessi, Jonathan, Plawecki, Martin H., Harezlak, Jaroslaw, Kareken, David, Goñi, Joaquín
Human brain function dynamically adjusts to ever-changing stimuli from the external environment. Studies characterizing brain functional reconfiguration are nevertheless scarce. Here we present a principled mathematical framework to quantify brain fu
Externí odkaz:
http://arxiv.org/abs/2405.15905
Autor:
Moghaddam, Mahdi Movahedian
When developing a software system, a change in one part of the system may lead to unwanted changes in other parts of the system. These affected parts may interfere with system performance, so regression testing is used to deal with these disorders. T
Externí odkaz:
http://arxiv.org/abs/2206.05494
Autor:
Soleimani Moghaddam, Mahdi, Bahari, Ali, Houshani, Mahdieh, Jafari, Adeleh, Motallebi Tala Tapeh, Sogol
Publikováno v:
In Journal of Power Sources 30 November 2024 621
Publikováno v:
In Journal of Power Sources 1 June 2024 604
Visual navigation is often cast as a reinforcement learning (RL) problem. Current methods typically result in a suboptimal policy that learns general obstacle avoidance and search behaviours. For example, in the target-object navigation setting, the
Externí odkaz:
http://arxiv.org/abs/2103.00446
We humans can impeccably search for a target object, given its name only, even in an unseen environment. We argue that this ability is largely due to three main reasons: the incorporation of prior knowledge (or experience), the adaptation of it to th
Externí odkaz:
http://arxiv.org/abs/2004.03222
Akademický článek
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Publikováno v:
In International Journal of Hydrogen Energy 15 October 2023 48(85):33139-33154