Zobrazeno 1 - 10
of 13 989
pro vyhledávání: '"Keshari"'
Autor:
Sarhaddi-Dadian, Hossein
Publikováno v:
Studii de Preistorie / Studies of Prehistory. (18):147-160
Externí odkaz:
https://www.ceeol.com/search/article-detail?id=1021087
Autor:
Panigrahy, Krushnachandra, Karmakar, Biswarup, Sahoo, Jajati Keshari, Behera, Ratikanta, Mohapatra, Ram N.
The theory and computation of tensors with different tensor products play increasingly important roles in scientific computing and machine learning. Different products aim to preserve different algebraic properties from the matrix algebra, and the ch
Externí odkaz:
http://arxiv.org/abs/2409.08743
The outer inverse of tensors plays increasingly significant roles in computational mathematics, numerical analysis, and other generalized inverses of tensors. In this paper, we compute outer inverses with prescribed ranges and kernels of a given tens
Externí odkaz:
http://arxiv.org/abs/2409.07007
Autor:
Mollabashi, Ali, Rahimi-Keshari, Saleh
We show that randomness in quadratic bosonic Hamiltonians results in certain information scrambling diagnostics, mirroring those in chaotic systems. Specifically, for initial Gaussian states, we observe the disappearance of the memory effect in the e
Externí odkaz:
http://arxiv.org/abs/2408.12089
Cone Beam Computed Tomography (CBCT) and Panoramic X-rays are the most commonly used imaging modalities in dental health care. CBCT can produce three-dimensional views of a patient's head, providing clinicians with better diagnostic capability, where
Externí odkaz:
http://arxiv.org/abs/2408.09358
Recent studies have revealed that certain nuclear parameters are more dominant than others in governing global neutron star properties, such as its structure or oscillation mode characteristics. Although neutron stars can in general assumed to be col
Externí odkaz:
http://arxiv.org/abs/2408.00739
Autor:
Patra, Subhajit, Panda, Sonali, Parida, Bikram Keshari, Arya, Mahima, Jacobs, Kurt, Bondar, Denys I., Sen, Abhijit
Physics-informed neural networks have proven to be a powerful tool for solving differential equations, leveraging the principles of physics to inform the learning process. However, traditional deep neural networks often face challenges in achieving h
Externí odkaz:
http://arxiv.org/abs/2407.18373
This paper introduces notions of the Drazin and the core-EP inverses on tensors via M-product. We propose a few properties of the Drazin and core-EP inverses of tensors, as well as effective tensor-based algorithms for calculating these inverses. In
Externí odkaz:
http://arxiv.org/abs/2405.16111
Publikováno v:
Eur. Phys. J. D 78, 60 (2024)
We have analytically determined the refractive index for the mechanical refraction of a relativistic particle for its all possible speeds. We have critically analysed the importance of Descartes' metaphysical theory and extended it in this regard. We
Externí odkaz:
http://arxiv.org/abs/2405.14912
Quantum kernel methods are a proposal for achieving quantum computational advantage in machine learning. They are based on a hybrid classical-quantum computation where a function called the quantum kernel is estimated by a quantum device while the re
Externí odkaz:
http://arxiv.org/abs/2405.12378