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pro vyhledávání: '"SINGH, ANUP"'
We construct a Lagrangian multiform for the class of cyclotomic (rational) Gaudin models by formulating its hierarchy within the Lie dialgebra framework of Semenov-Tian-Shansky and by using the framework of Lagrangian multiforms on coadjoint orbits.
Externí odkaz:
http://arxiv.org/abs/2405.12837
Fibonacci Neural Network Approach for Numerical Solutions of Fractional Order Differential Equations
Autor:
Dwivedi, Kushal Dhar, Singh, Anup
In this paper, the authors propose the utilization of Fibonacci Neural Networks (FNN) for solving arbitrary order differential equations. The FNN architecture comprises input, middle, and output layers, with various degrees of Fibonacci polynomials s
Externí odkaz:
http://arxiv.org/abs/2405.04200
Lagrangian multiforms provide a variational framework to describe integrable hierarchies. The case of Lagrangian $1$-forms covers finite-dimensional integrable systems. We use the theory of Lie dialgebras introduced by Semenov-Tian-Shansky to constru
Externí odkaz:
http://arxiv.org/abs/2307.07339
If $f(z)$ is a modular form of weight $k$, then the differential operator $\vartheta_k$ defined by $\vartheta_k(f) = \frac{1}{2\pi i} \frac{d}{dz}f(z) - \frac{k}{12} E_2(z) f(z)$ (known as the Ramanujan-Serre derivative map) is a modular form of weig
Externí odkaz:
http://arxiv.org/abs/2303.02921
Audio fingerprinting systems must efficiently and robustly identify query snippets in an extensive database. To this end, state-of-the-art systems use deep learning to generate compact audio fingerprints. These systems deploy indexing methods, which
Externí odkaz:
http://arxiv.org/abs/2211.11060
Autor:
Rangan, N. Mohan1 (AUTHOR), Singh, Anup Kumar1 (AUTHOR), Yadav, Rekha C.1 (AUTHOR) rekha.pt@rediffmail.com, Roy, Indranil Deb1 (AUTHOR), Tomar, Kapil1 (AUTHOR), Singh, Neha2 (AUTHOR), R, Vasanthanarayanan1 (AUTHOR)
Publikováno v:
Journal of Rare Diseases. 10/9/2024, Vol. 3 Issue 1, p1-10. 10p.
An ideal audio retrieval system efficiently and robustly recognizes a short query snippet from an extensive database. However, the performance of well-known audio fingerprinting systems falls short at high signal distortion levels. This paper present
Externí odkaz:
http://arxiv.org/abs/2210.08624
Autor:
Martin, Hector Garcia, Radivojevic, Tijana, Zucker, Jeremy, Bouchard, Kristofer, Sustarich, Jess, Peisert, Sean, Arnold, Dan, Hillson, Nathan, Babnigg, Gyorgy, Marti, Jose Manuel, Mungall, Christopher J., Beckham, Gregg T., Waldburger, Lucas, Carothers, James, Sundaram, ShivShankar, Agarwal, Deb, Simmons, Blake A., Backman, Tyler, Banerjee, Deepanwita, Tanjore, Deepti, Ramakrishnan, Lavanya, Singh, Anup
Self-driving labs (SDLs) combine fully automated experiments with artificial intelligence (AI) that decides the next set of experiments. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is pr
Externí odkaz:
http://arxiv.org/abs/2210.09085
Autor:
Meng, Fan, Li, Tiane, Singh, Anup K., Wang, Yingying, Attiyeh, Marc, Kohram, Fatemeh, Feng, Qianhua, Li, Yun R., Shen, Binghui, Williams, Terence, Liu, Yilun, Raoof, Mustafa
Publikováno v:
In Cell Reports 22 October 2024 43(10)
Autor:
Bhol, Nitish Kumar, Bhanjadeo, Madhabi Madhusmita, Singh, Anup Kumar, Dash, Umesh Chandra, Ojha, Rakesh Ranjan, Majhi, Sanatan, Duttaroy, Asim K., Jena, Atala Bihari
Publikováno v:
In Biomedicine & Pharmacotherapy September 2024 178