Zobrazeno 1 - 10
of 8 826
pro vyhledávání: '"A A, Durrani"'
When training data are distributed across{ time or space,} covariate shift across fragments of training data biases cross-validation, compromising model selection and assessment. We present \textit{Fragmentation-Induced covariate-shift Remediation} (
Externí odkaz:
http://arxiv.org/abs/2411.06499
Autor:
Tang, Zhifeng, Yang, Nan, Durrani, Salman, Zhou, Xiangyun, Juntti, Markku, Jornet, Josep Miquel
In this paper, we develop a novel analytical framework for a three-dimensional (3D) indoor terahertz (THz) communication system. Our proposed model incorporates more accurate modeling of wall blockages via Manhattan line processes and precise modelin
Externí odkaz:
http://arxiv.org/abs/2410.04681
Autor:
Liang, Jing, Das, Dibyendu, Song, Daeun, Shuvo, Md Nahid Hasan, Durrani, Mohammad, Taranath, Karthik, Penskiy, Ivan, Manocha, Dinesh, Xiao, Xuesu
Navigating large-scale outdoor environments requires complex reasoning in terms of geometric structures, environmental semantics, and terrain characteristics, which are typically captured by onboard sensors such as LiDAR and cameras. While current mo
Externí odkaz:
http://arxiv.org/abs/2409.14262
Autor:
Mousi, Basel, Durrani, Nadir, Ahmad, Fatema, Hasan, Md. Arid, Hasanain, Maram, Kabbani, Tameem, Dalvi, Fahim, Chowdhury, Shammur Absar, Alam, Firoj
Arabic, with its rich diversity of dialects, remains significantly underrepresented in Large Language Models, particularly in dialectal variations. We address this gap by introducing seven synthetic datasets in dialects alongside Modern Standard Arab
Externí odkaz:
http://arxiv.org/abs/2409.11404
Despite their remarkable ability to capture linguistic nuances across diverse languages, questions persist regarding the degree of alignment between languages in multilingual embeddings. Drawing inspiration from research on high-dimensional represent
Externí odkaz:
http://arxiv.org/abs/2405.14535
Interpreting and understanding the predictions made by deep learning models poses a formidable challenge due to their inherently opaque nature. Many previous efforts aimed at explaining these predictions rely on input features, specifically, the word
Externí odkaz:
http://arxiv.org/abs/2404.12545
Autor:
Chan, Chiu Chun, Alvi, Sheeraz A., Zhou, Xiangyun, Durrani, Salman, Wilson, Nicholas, Yebra, Marta
The threat posed by wildfires or bushfires has become a severe global issue due to the increase in human activities in forested areas and the impact of climate change. Consequently, there is a surge in the development of automatic wildfire detection
Externí odkaz:
http://arxiv.org/abs/2312.10919
Autor:
Hassan Farooq Afridi, Diyar Khan, Waseem Akhtar Khan, Hamza Jamal, Afaq Ahmad Durrani, Muhammad Ali Afridi, Abdalrhman Milad
Publikováno v:
Discover Civil Engineering, Vol 1, Iss 1, Pp 1-15 (2024)
Abstract This study objective to assess the effects of Waste Engine Oil (WEO) and Sasobit on improving the rheological and physicochemical properties of Reclaimed Asphalt Pavement (RAP), both of which are considered waste materials. Seven asphalt mix
Externí odkaz:
https://doaj.org/article/0972527696b6489097444ad700eb11ae
Autor:
Zia-ul-Sabah, Saif Aboud M. Alqahtani, Bandar Hezam Alghamdi, Javed Iqbal Wani, Shahid Aziz, Humayoun Khan Durrani, Ayyub Ali Patel, Imran Rangraze, Saleem Javaid Wani
Publikováno v:
BMC Cardiovascular Disorders, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Background Type-D personality is an established predisposing factor for various diseases. Type-D traits have been shown to pose a 26% increased risk of coronary artery disease after controlling for other confounding factors. Significant asso
Externí odkaz:
https://doaj.org/article/c31971de08644e10a180bd075cb8b330
Despite the revolution caused by deep NLP models, they remain black boxes, necessitating research to understand their decision-making processes. A recent work by Dalvi et al. (2022) carried out representation analysis through the lens of clustering l
Externí odkaz:
http://arxiv.org/abs/2308.10263