Zobrazeno 1 - 10
of 37 605
pro vyhledávání: '"Peyman, A."'
Autor:
Lozano-Martín, Daniel, Khanipour, Peyman, Kipphardt, Heinrich, Tuma, Dirk, Chamorro, César R.
Publikováno v:
International Journal of Hydrogen Energy Volume 48, Issue 23, 2023, Pages 8645-8667
For the gradual introduction of hydrogen in the energy market, the study of the properties of mixtures of hydrogen with typical components of natural gas (NG) and liquefied petroleum gas (LPG) is of great importance. This work aims to provide accurat
Externí odkaz:
http://arxiv.org/abs/2409.03647
Autor:
Polson, Lucas, Esquinas, Pedro, Kurkowska, Sara, Li, Chenguang, Sheikhzadeh, Peyman, Abbassi, Mehrshad, Farzanehfar, Saeed, Mirabedian, Seyyede, Uribe, Carlos, Rahmim, Arman
Modeling of the collimator-detector response (CDR) in SPECT reconstruction enables improved resolution and more accurate quantitation, especially for higher energy imaging (e.g.Lu-177 and Ac-225). Such modeling, however, can pose a significant comput
Externí odkaz:
http://arxiv.org/abs/2409.03100
Autor:
Lozano-Martín, Daniel, Pazoki, Fatemeh, Kipphardt, Heinrich, Khanipour, Peyman, Tuma, Dirk, Horrillo, Alfonso, Chamorro, César R.
Publikováno v:
International Journal of Hydrogen Energy Volume 70, 2024, Pages 118-135
The injection of hydrogen into the natural-gas grid is an alternative during the process of a gradual decarbonization of the heat and power supply. When dealing with hydrogen-enriched natural gas mixtures, the performance of the reference equations o
Externí odkaz:
http://arxiv.org/abs/2409.01702
With the recent unprecedented advancements in Artificial Intelligence (AI) computing, progress in Large Language Models (LLMs) is accelerating rapidly, presenting challenges in establishing clear guidelines, particularly in the field of security. Tha
Externí odkaz:
http://arxiv.org/abs/2409.00571
Autor:
Bethany, Mazal, Bethany, Emet, Wherry, Brandon, Chiang, Cho-Yu, Vishwamitra, Nishant, Rios, Anthony, Najafirad, Peyman
Event detection and text reasoning have become critical applications across various domains. While LLMs have recently demonstrated impressive progress in reasoning abilities, they often struggle with event detection, particularly due to the absence o
Externí odkaz:
http://arxiv.org/abs/2409.00209
Software security remains a critical concern, particularly as junior developers, often lacking comprehensive knowledge of security practices, contribute to codebases. While there are tools to help developers proactively write secure code, their actua
Externí odkaz:
http://arxiv.org/abs/2409.00199
This study proposes a machine learning-based Model Predictive Control (MPC) approach for controlling Air Handling Unit (AHU) systems by employing an Internet of Things (IoT) framework. The proposed framework utilizes an Artificial Neural Network (ANN
Externí odkaz:
http://arxiv.org/abs/2408.13294
We study the problem of estimating the optimal Q-function of $\gamma$-discounted Markov decision processes (MDPs) under the synchronous setting, where independent samples for all state-action pairs are drawn from a generative model at each iteration.
Externí odkaz:
http://arxiv.org/abs/2408.06544
Autor:
Zhu, William Y., Ye, Keren, Ke, Junjie, Yu, Jiahui, Guibas, Leonidas, Milanfar, Peyman, Yang, Feng
Recognizing and disentangling visual attributes from objects is a foundation to many computer vision applications. While large vision language representations like CLIP had largely resolved the task of zero-shot object recognition, zero-shot visual a
Externí odkaz:
http://arxiv.org/abs/2408.04102
Large Language Models (LLMs) have demonstrated impressive capabilities in natural language tasks, but their safety and morality remain contentious due to their training on internet text corpora. To address these concerns, alignment techniques have be
Externí odkaz:
http://arxiv.org/abs/2408.02651