Zobrazeno 1 - 10
of 45 175
pro vyhledávání: '"Verma, A. K."'
Autor:
Verma, Mahendra K.
Hydrodynamic turbulence exhibits nonequilibrium behaviour with $k^{-5/3}$ energy spectrum, and equilibrium behaviour with $k^{d-1}$ energy spectrum and zero viscosity, where $d$ is the space dimension. Using recursive renormalization group {in Craya-
Externí odkaz:
http://arxiv.org/abs/2408.07573
This paper introduces nonlinear fractional Lane-Emden equations of the form, $$ D^{\alpha} y(x) + \frac{\lambda}{x^\beta}~ D^{\beta} y(x) + f(y) =0, ~ ~1 < \alpha \leq 2, ~~ 0< \beta \leq 1, ~~ 0 < x < 1,$$ subject to boundary conditions, $$ y'(0) =\
Externí odkaz:
http://arxiv.org/abs/2408.10212
Despite the rapid advancement in the field of image recognition, the processing of high-resolution imagery remains a computational challenge. However, this processing is pivotal for extracting detailed object insights in areas ranging from autonomous
Externí odkaz:
http://arxiv.org/abs/2405.07166
Autor:
Kumar, Saurabh
Publikováno v:
Social Scientist, 2021 Jan 01. 491/2 (572-573), 93-96.
Externí odkaz:
https://www.jstor.org/stable/27026935
Autor:
Bhat, Meghana, Dubey, Saipriya, Masuti, Shreedevi K., Okuma, Tomohiro, Verma, Jugal K., Watanabe, Kei-ichi, Yoshida, Ken-ichi
Let $(A, \mathfrak{m})$ be a Gorenstein local ring, and $\mathcal{F} =\{F_n \}_{n\in \mathbb{Z}}$ a Hilbert filtration. In this paper, we give a criterion for Gorensteinness of the associated graded ring of $\mathcal{F}$ in terms of the Hilbert coeff
Externí odkaz:
http://arxiv.org/abs/2404.14189
Continual Learning (CL) enables machine learning models to learn from continuously shifting new training data in absence of data from old tasks. Recently, pretrained vision transformers combined with prompt tuning have shown promise for overcoming ca
Externí odkaz:
http://arxiv.org/abs/2403.20317
This article investigates the computational aspects of the $\varepsilon$-multiplicity. Primarily, we show that the $\varepsilon$-multiplicity of a homogeneous ideal $I$ in a two-dimensional standard graded domain of finite type over an algebraically
Externí odkaz:
http://arxiv.org/abs/2402.11935
Autor:
Maurya, Seetaram, Verma, Nishchal K.
Various methods for designing input features have been proposed for fault recognition in rotating machines using one-dimensional raw sensor data. The available methods are complex, rely on empirical approaches, and may differ depending on the conditi
Externí odkaz:
http://arxiv.org/abs/2402.09957
Autor:
Gupta, Bivek, Verma, Amit K.
This comprehensive review paper delves into the intricacies of advanced Fourier type integral transforms and their mathematical properties, with a particular focus on fractional Fourier transform (FrFT), linear canonical transform (LCT), quadratic ph
Externí odkaz:
http://arxiv.org/abs/2402.06645
This paper proposes a simple but highly efficient expansion-based model for continual learning. The recent feature transformation, masking and factorization-based methods are efficient, but they grow the model only over the global or shared parameter
Externí odkaz:
http://arxiv.org/abs/2312.01188