Zobrazeno 1 - 10
of 98 640
pro vyhledávání: '"Taha IN"'
Autor:
Askari, Mohammad Taha, Lampe, Lutz
Optimizing the input probability distribution of a discrete-time channel is a standard step in the information-theoretic analysis of digital communication systems. Nevertheless, many practical communication systems transmit uniformly and independentl
Externí odkaz:
http://arxiv.org/abs/2412.09581
Quantifying how individuals react to social influence is crucial for tackling collective political behavior online. While many studies of opinion in public forums focus on social feedback, they often overlook the potential for human interactions to r
Externí odkaz:
http://arxiv.org/abs/2412.05741
Autor:
Zheng, Xue Xian, Rahma, M. M. Ur, Taha, Bilal, Masood, Mudassir, Hatzinakos, Dimitrios, Al-Naffouri, Tareq
Camera-based photoplethysmography (PPG) obtained from smartphones has shown great promise for personalized healthcare and secure authentication. This paper presents a multimodal biometric system that integrates PPG signals extracted from videos with
Externí odkaz:
http://arxiv.org/abs/2412.05660
Advancements in computational fluid mechanics have largely relied on Newtonian frameworks, particularly through the direct simulation of Navier-Stokes equations. In this work, we propose an alternative computational framework that employs variational
Externí odkaz:
http://arxiv.org/abs/2412.05525
Cooperation between humans and machines is increasingly vital as artificial intelligence (AI) becomes more integrated into daily life. Research indicates that people are often less willing to cooperate with AI agents than with humans, more readily ex
Externí odkaz:
http://arxiv.org/abs/2412.05214
Autor:
Belaloui, Nacer Eddine, Tounsi, Abdellah, Khamadja, Rabah Abdelmouheymen, Louamri, Mohamed Messaoud, Benslama, Achour, Neira, David E. Bernal, Rouabah, Mohamed Taha
While numerical simulations are presented in most papers introducing new methods to enhance the VQE performance, comprehensive, comparative, and applied studies remain relatively rare. We present a comprehensive, yet concise guide for the implementat
Externí odkaz:
http://arxiv.org/abs/2412.02606
Autor:
Fotouhi, Milad, Bahadori, Mohammad Taha, Feyisetan, Oluwaseyi, Arabshahi, Payman, Heckerman, David
The existing algorithms for identification of neurons responsible for undesired and harmful behaviors do not consider the effects of confounders such as topic of the conversation. In this work, we show that confounders can create spurious correlation
Externí odkaz:
http://arxiv.org/abs/2412.02893
Advanced driver assistance systems (ADAS) enabled by automotive radars have significantly enhanced vehicle safety and driver experience. However, the extensive use of radars in dense road conditions introduces mutual interference, which degrades dete
Externí odkaz:
http://arxiv.org/abs/2412.00441
In this paper, we present a novel approach for fluid dynamic simulations by harnessing the capabilities of Physics-Informed Neural Networks (PINNs) guided by the newly unveiled principle of minimum pressure gradient (PMPG). In a PINN formulation, the
Externí odkaz:
http://arxiv.org/abs/2411.15410
Recent advancements in vision-language models (VLMs), such as CLIP, have demonstrated substantial success in self-supervised representation learning for vision tasks. However, effectively adapting VLMs to downstream applications remains challenging,
Externí odkaz:
http://arxiv.org/abs/2411.15232