Zobrazeno 1 - 10
of 37 037
pro vyhledávání: '"Ahmadi P."'
Modelling the large deformation of hyperelastic solids under plane stress conditions for arbitrary compressible and nearly incompressible material models is challenging. This is in contrast to the case of full incompressibility where the out-of-plane
Externí odkaz:
http://arxiv.org/abs/2410.22562
Autor:
Ghomroudi, Parisa Ahmadi, Scaltritti, Michele, Monachesi, Bianca, Wongupparaj, Peera, Job, Remo, Grecucci, Alessandro
In daily interactions, emotions are frequently conveyed and triggered through verbal exchanges. Sometimes, we must modulate our emotional reactions to align with societal norms. Among the emotional words, taboo words represent a specific category tha
Externí odkaz:
http://arxiv.org/abs/2410.19953
Numerous studies have shown that generalized uncertainty principle (GUP) removes the Chandrasekhar limit, which can be restored using a negative GUP parameter. This study indicates that observational phantom dark energy also requires an extended unce
Externí odkaz:
http://arxiv.org/abs/2410.17080
Autor:
Klaver, Yvan, Morsche, Randy te, Botter, Roel A., Hashemi, Batoul, Frare, Bruno L. Segat, Mishra, Akhileshwar, Ye, Kaixuan, Mbonde, Hamidu, Ahmadi, Pooya Torab, Taleghani, Niloofar Majidian, Jonker, Evan, Braamhaar, Redlef B. G., Selvaganapathy, Ponnambalam Ravi, Mascher, Peter, van der Slot, Peter J. M., Bradley, Jonathan D. B., Marpaung, David
Seamlessly integrating stimulated Brillouin scattering (SBS) in a low-loss and mature photonic integration platform remains a complicated task. Virtually all current approaches fall short in simultaneously achieving strong SBS, low losses, and techno
Externí odkaz:
http://arxiv.org/abs/2410.16263
In today's world, the significance of explainable AI (XAI) is growing in robotics and point cloud applications, as the lack of transparency in decision-making can pose considerable safety risks, particularly in autonomous systems. As these technologi
Externí odkaz:
http://arxiv.org/abs/2410.15374
The optimal training of a vision transformer for brain encoding depends on three factors: model size, data size, and computational resources. This study investigates these three pillars, focusing on the effects of data scaling, model scaling, and hig
Externí odkaz:
http://arxiv.org/abs/2410.19810
Publikováno v:
Trans. Theor. Math. Phys. (TTMP), vol 1(4), 2024
In solving the Brans-Dicke (BD) equations in the BD theory of gravity, their linear independence is important. This is due to fact that in solving these equations in cosmology, if the number of unknown quantities is equal to the number of independent
Externí odkaz:
http://arxiv.org/abs/2410.13316
Autor:
Toscano, Juan Diego, Oommen, Vivek, Varghese, Alan John, Zou, Zongren, Daryakenari, Nazanin Ahmadi, Wu, Chenxi, Karniadakis, George Em
Physics-Informed Neural Networks (PINNs) have emerged as a key tool in Scientific Machine Learning since their introduction in 2017, enabling the efficient solution of ordinary and partial differential equations using sparse measurements. Over the pa
Externí odkaz:
http://arxiv.org/abs/2410.13228
Autor:
Nemati, Narin, Kasani, Amin Ahmadi
Wind energy has emerged as one of the most vital and economically viable forms of renewable energy. The integration of wind energy sources into power grids across the globe has been increasing substantially, largely due to the higher levels of uncert
Externí odkaz:
http://arxiv.org/abs/2410.11139
Autor:
Ahmadi, Sahar, Cheraghian, Ali, Saberi, Morteza, Abir, Md. Towsif, Dastmalchi, Hamidreza, Hussain, Farookh, Rahman, Shafin
Recent advances in deep learning for processing point clouds hold increased interest in Few-Shot Class Incremental Learning (FSCIL) for 3D computer vision. This paper introduces a new method to tackle the Few-Shot Continual Incremental Learning (FSCI
Externí odkaz:
http://arxiv.org/abs/2410.09237