Zobrazeno 1 - 10
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pro vyhledávání: '"Akram, A"'
Landmines remain a pervasive threat in conflict-affected regions worldwide, exacting a toll on innocent lives. Shockingly, every 95 minutes, another individual becomes a victim of these lethal explosive devices (Landmines Monitor 2022 2022), with a s
Externí odkaz:
http://arxiv.org/abs/2410.23998
The effect of regularizers such as weight decay when training deep neural networks is not well understood. We study the influence of weight decay as well as $L2$-regularization when training neural network models in which parameter matrices interact
Externí odkaz:
http://arxiv.org/abs/2410.23819
Beam management is an important technique to improve signal strength and reduce interference in wireless communication systems. Recently, there has been increasing interest in using diverse sensing modalities for beam management. However, it remains
Externí odkaz:
http://arxiv.org/abs/2410.19859
Autor:
Akram, Usman, Vikalo, Haris
We investigate whether transformers can learn to track a random process when given observations of a related process and parameters of the dynamical system that relates them as context. More specifically, we consider a finite-dimensional state-space
Externí odkaz:
http://arxiv.org/abs/2410.16546
The bimodal metallicity distribution of globular clusters (GCs) in massive galaxies implies two distinct sub-populations: metal-poor and metal-rich. Using the recent data of \textit{Gaia} we highlighted three distinct dissimilarities between metal-po
Externí odkaz:
http://arxiv.org/abs/2410.16276
We present an advanced approach to medical question-answering (QA) services, using fine-tuned Large Language Models (LLMs) to improve the accuracy and reliability of healthcare information. Our study focuses on optimizing models like LLaMA-2 and Mist
Externí odkaz:
http://arxiv.org/abs/2410.16088
Autor:
Liu, Xinran, Martín, Rocío Díaz, Bai, Yikun, Shahbazi, Ashkan, Thorpe, Matthew, Aldroubi, Akram, Kolouri, Soheil
The optimal transport (OT) problem has gained significant traction in modern machine learning for its ability to: (1) provide versatile metrics, such as Wasserstein distances and their variants, and (2) determine optimal couplings between probability
Externí odkaz:
http://arxiv.org/abs/2410.12176
Autor:
Qian, Cheng, Shi, Xianglong, Yao, Shanshan, Liu, Yichen, Zhou, Fengming, Zhang, Zishu, Akram, Junaid, Braytee, Ali, Anaissi, Ali
We present a refined approach to biomedical question-answering (QA) services by integrating large language models (LLMs) with Multi-BERT configurations. By enhancing the ability to process and prioritize vast amounts of complex biomedical data, this
Externí odkaz:
http://arxiv.org/abs/2410.12856
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:
Akram, Junaid, Anaissi, Ali
We present an innovative framework that integrates consumer-grade drones into bushfire management, addressing both service improvement and data privacy concerns under Australia's Privacy Act 1988. This system establishes a marketplace where bushfire
Externí odkaz:
http://arxiv.org/abs/2410.05653