Zobrazeno 1 - 10
of 620
pro vyhledávání: '"Md, Yousuf"'
Generative large language models (LLMs) exhibit impressive capabilities, which can be further augmented by integrating a pre-trained vision model into the original LLM to create a multimodal LLM (MLLM). However, this integration often significantly d
Externí odkaz:
http://arxiv.org/abs/2410.19925
Embeddings produced by pre-trained deep neural networks (DNNs) are widely used; however, their efficacy for downstream tasks can vary widely. We study the factors influencing transferability and out-of-distribution (OOD) generalization of pre-trained
Externí odkaz:
http://arxiv.org/abs/2405.15018
Continual learning (CL) in deep neural networks (DNNs) involves incrementally accumulating knowledge in a DNN from a growing data stream. A major challenge in CL is that non-stationary data streams cause catastrophic forgetting of previously learned
Externí odkaz:
http://arxiv.org/abs/2308.13646
Autor:
Harun, Md Yousuf, Kanan, Christopher
Pre-trained deep neural networks (DNNs) are being widely deployed by industry for making business decisions and to serve users; however, a major problem is model decay, where the DNN's predictions become more erroneous over time, resulting in revenue
Externí odkaz:
http://arxiv.org/abs/2306.01904
Publikováno v:
Alexandria Engineering Journal, Vol 104, Iss , Pp 66-84 (2024)
The goal of this work is to further improve our knowledge of the nonlinear radiative second-grade nano fluid flow boundary layer phenomena which is associated with an Arrhenius activation energy, a sinusoidal magnetic field, and a stretched periphera
Externí odkaz:
https://doaj.org/article/2aa9585ca45b4cd6bdb732b308535138
Supervised Continual learning involves updating a deep neural network (DNN) from an ever-growing stream of labeled data. While most work has focused on overcoming catastrophic forgetting, one of the major motivations behind continual learning is bein
Externí odkaz:
http://arxiv.org/abs/2303.18171
In supervised continual learning, a deep neural network (DNN) is updated with an ever-growing data stream. Unlike the offline setting where data is shuffled, we cannot make any distributional assumptions about the data stream. Ideally, only one pass
Externí odkaz:
http://arxiv.org/abs/2303.10725
Autor:
Mahir Tajwar, Mahfuzur Rahman, Shamiha Shafinaz Shreya, Nazmus Sakib, Md. Yousuf Gazi, Mahmudul Hasan, Majidul Islam, Mir Md Tasnim Alam, Anwar Zahid
Publikováno v:
Journal of Trace Elements and Minerals, Vol 10, Iss , Pp 100197- (2024)
Groundwater is the main source of potable water in rural regions of Bangladesh. Still, contamination with potentially harmful metals due to natural processes and anthropogenic activities leads to various health impacts. The focus of this research was
Externí odkaz:
https://doaj.org/article/17acda4efb51468c823cbe5a25525c5e
Autor:
Saina Yan, Fen Pei, Jingfnag Si, Md. Yousuf Ali Khan, Sihai Ou, Yang Yang, Zongsheng Zhao, Alfredo Pauciullo, Yi Zhang
Publikováno v:
Animal Biotechnology, Vol 35, Iss 1 (2024)
Weaning weight is a key indicator of the early growth performance of cattle. An understanding of the genetic mechanisms underlying weaning weight will help increase the accuracy of selection of breeding animals. In order to identify candidate genes a
Externí odkaz:
https://doaj.org/article/22b7887726b24737b6bcac40ac94f5ab
Autor:
Md. Yousuf Ali, Mizanur Rahman
Publikováno v:
Heliyon, Vol 10, Iss 22, Pp e40021- (2024)
Statistical analysis (SA) stands as an indispensable tool in materials science and engineering, aiding in the understanding and optimization of heat and mass transport processes. This study delves into the interplay between periodic magneto-hydrodyna
Externí odkaz:
https://doaj.org/article/b8382952d88e438eb136d4a93569e1c2