Zobrazeno 1 - 10
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pro vyhledávání: '"P. Ghose"'
Publikováno v:
Епістемологічні дослідження у філософії, соціальних і політичних науках, Vol 7, Iss 1 (2024)
In this study, first of all, it was important to analyze this technique of returning to the ancient tradition of two outstanding thinkers of the 20th century. M. Heidegger and Sri Aurobindo Ghosh in order to understand to what extent the language of
Externí odkaz:
https://doaj.org/article/b87e0fc56f13434facf617601d42fa81
Autor:
Anandh, Thivin, Ghose, Divij, Jain, Himanshu, Sunkad, Pratham, Ganesan, Sashikumaar, John, Volker
This paper proposes and studies two extensions of applying hp-variational physics-informed neural networks, more precisely the FastVPINNs framework, to convection-dominated convection-diffusion-reaction problems. First, a term in the spirit of a SUPG
Externí odkaz:
http://arxiv.org/abs/2411.09329
High-resolution seismic reflections are essential for imaging and monitoring applications. In seismic land surveys using sources and receivers at the surface, surface waves often dominate, masking the reflections. In this study, we demonstrate the ef
Externí odkaz:
http://arxiv.org/abs/2411.02620
Contextual advertising serves ads that are aligned to the content that the user is viewing. The rapid growth of video content on social platforms and streaming services, along with privacy concerns, has increased the need for contextual advertising.
Externí odkaz:
http://arxiv.org/abs/2410.22233
Autor:
Srivastava, Sanchit, Ghose, Shohini
Quantum states of multiple qubits can violate Bell-type inequalities when there is entanglement present between the qubits, indicating nonlocal behaviour of correlations. We analyze the relation between multipartite entanglement and genuine multipart
Externí odkaz:
http://arxiv.org/abs/2409.10888
Autor:
Anandh, Thivin, Ghose, Divij, Tyagi, Ankit, Gupta, Abhineet, Sarkar, Suranjan, Ganesan, Sashikumaar
Physics-informed neural networks (PINNs) are able to solve partial differential equations (PDEs) by incorporating the residuals of the PDEs into their loss functions. Variational Physics-Informed Neural Networks (VPINNs) and hp-VPINNs use the variati
Externí odkaz:
http://arxiv.org/abs/2409.04143
Alzheimer's Disease (AD) is a neurodegenerative disease affecting millions of individuals across the globe. As the prevalence of this disease continues to rise, early diagnosis is crucial to improve clinical outcomes. Neural networks, specifically Co
Externí odkaz:
http://arxiv.org/abs/2409.02961
Autor:
Ghose, Saugata
The first years of the 2000s led to an inflection point in computer architectures: while the number of available transistors on a chip continued to grow, crucial transistor scaling properties started to break down and result in increasing power consu
Externí odkaz:
http://arxiv.org/abs/2408.12999
Classical chaos arises from the inherent non-linearity of dynamical systems. However, quantum maps are linear; therefore, the definition of chaos is not straightforward. To address this, we study a quantum system that exhibits chaotic behavior in its
Externí odkaz:
http://arxiv.org/abs/2408.05869
Point cloud understanding is an inherently challenging problem because of the sparse and unordered structure of the point cloud in the 3D space. Recently, Contrastive Vision-Language Pre-training (CLIP) based point cloud classification model i.e. Poi
Externí odkaz:
http://arxiv.org/abs/2408.03545