Zobrazeno 1 - 10
of 10 849
pro vyhledávání: '"Hosein P."'
Autor:
Wagner, Jan-Samuel, DeCaprio, Dave, Raja, Abishek Chiffon Muthu, Holman, Jonathan M., Brady, Lauren K., Cheung, Sky C., Barzekar, Hosein, Yang, Eric, Martinez II, Mark Anthony, Soong, David, Sridhar, Sriram, Si, Han, Higgs, Brandon W., Hamadeh, Hisham, Ogden, Scott
We introduce Controller-Embedded Language Model Interactions (CELI), a framework that integrates control logic directly within language model (LM) prompts, facilitating complex, multi-stage task execution. CELI addresses limitations of existing promp
Externí odkaz:
http://arxiv.org/abs/2410.14627
Autor:
Mozafari, Mohammad, Hasani, Hosein, Vahidimajd, Reza, Fereydooni, Mohamadreza, Baghshah, Mahdieh Soleymani
In recent years, few-shot segmentation (FSS) models have emerged as a promising approach in medical imaging analysis, offering remarkable adaptability to segment novel classes with limited annotated data. Existing approaches to few-shot segmentation
Externí odkaz:
http://arxiv.org/abs/2410.09967
We examine a new scenario to model the outer halo globular cluster (GC) Pal 14 over its lifetime by performing a comprehensive set of direct N-body calculations. We assume Pal 14 was born in a now detached/disrupted dwarf galaxy with a strong tidal f
Externí odkaz:
http://arxiv.org/abs/2410.06036
Autor:
Ghaznavi, Mahdi, Asadollahzadeh, Hesam, Noohdani, Fahimeh Hosseini, Tabar, Soroush Vafaie, Hasani, Hosein, Alvanagh, Taha Akbari, Rohban, Mohammad Hossein, Baghshah, Mahdieh Soleymani
Classifiers trained with Empirical Risk Minimization (ERM) tend to rely on attributes that have high spurious correlation with the target. This can degrade the performance on underrepresented (or 'minority') groups that lack these attributes, posing
Externí odkaz:
http://arxiv.org/abs/2410.05345
Transformer-based language models have shown an excellent ability to effectively capture and utilize contextual information. Although various analysis techniques have been used to quantify and trace the contribution of single contextual cues to a tar
Externí odkaz:
http://arxiv.org/abs/2410.03447
Neural speech models build deeply entangled internal representations, which capture a variety of features (e.g., fundamental frequency, loudness, syntactic category, or semantic content of a word) in a distributed encoding. This complexity makes it d
Externí odkaz:
http://arxiv.org/abs/2410.03037
Autor:
Ghasemi, S. Mojtaba, Rostami-Shirazi, Ali, Khalaj, Pouria, Zonoozi, Akram Hasani, Haghi, Hosein
We investigate the impact of primordial mass segregation on the formation and evolution of dark star clusters (DSCs). Considering a wide range of initial conditions, we conducted $N$-body simulations of globular clusters (GCs) around the Milky Way. I
Externí odkaz:
http://arxiv.org/abs/2409.15280
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
Causal Bayesian networks (CBN) are popular graphical probabilistic models that encode causal relations among variables. Learning their graphical structure from observational data has received a lot of attention in the literature. When there exists no
Externí odkaz:
http://arxiv.org/abs/2408.11181
The Nambu-Jona-Lasinio (NJL) model and specifically its extension to color superconductivity (CSC) is a popular effective model for investigating dense quark matter. However, the reliability of its results is challenged by cutoff artifacts, which eme
Externí odkaz:
http://arxiv.org/abs/2408.06704