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pro vyhledávání: '"Kathpalia A"'
Autor:
Kathpalia, Aditi, Nagaraj, Nithin
Signal processing and Information theory are two disparate fields used for characterizing signals for various scientific and engineering applications. Spectral/Fourier analysis, a technique employed in signal processing, helps estimation of power at
Externí odkaz:
http://arxiv.org/abs/2309.11640
Autor:
Kathpalia, Aditi, Nagaraj, Nithin
Compressed sensing is a scheme that allows for sparse signals to be acquired, transmitted and stored using far fewer measurements than done by conventional means employing Nyquist sampling theorem. Since many naturally occurring signals are sparse (i
Externí odkaz:
http://arxiv.org/abs/2210.11420
Distinguishing cause from effect is a scientific challenge resisting solutions from mathematics, statistics, information theory and computer science. Compression-Complexity Causality (CCC) is a recently proposed interventional measure of causality, i
Externí odkaz:
http://arxiv.org/abs/2204.11731
Discovering cause-effect from observational data is an important but challenging problem in science and engineering. In this work, a recently proposed brain inspired learning algorithm namely-\emph{Neurochaos Learning} (NL) is used for the classifica
Externí odkaz:
http://arxiv.org/abs/2201.12181
The science of causality explains/determines 'cause-effect' relationship between the entities of a system by providing mathematical tools for the purpose. In spite of all the success and widespread applications of machine-learning (ML) algorithms, th
Externí odkaz:
http://arxiv.org/abs/2112.03085
Autor:
Kathpalia, Meghavi, Mishra, Pinki, Majid, Afsha, Khan, Mohd. Ashif, Sharma, Anurag, Bhurani, Dinesh, Nidhi
Publikováno v:
In Journal of Neuroimmunology 15 July 2024 392
Autor:
Kumari, Megha, Checker, Vibha Gulyani, Kathpalia, Renu, Srivastava, Vikas, Singh, Indrakant Kumar, Singh, Archana
Publikováno v:
In Plant Physiology and Biochemistry May 2024 210
Akademický článek
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Autor:
Kathpalia, Aditi, Nagaraj, Nithin
Determining and measuring cause-effect relationships is fundamental to most scientific studies of natural phenomena. The notion of causation is distinctly different from correlation which only looks at association of trends or patterns in measurement
Externí odkaz:
http://arxiv.org/abs/1910.08750
Inspired by chaotic firing of neurons in the brain, we propose ChaosNet -- a novel chaos based artificial neural network architecture for classification tasks. ChaosNet is built using layers of neurons, each of which is a 1D chaotic map known as the
Externí odkaz:
http://arxiv.org/abs/1910.02423