Zobrazeno 1 - 10
of 3 614
pro vyhledávání: '"P. P. Deepthi"'
Publikováno v:
IEEE Access, Vol 10, Pp 17098-17112 (2022)
In mobile healthcare networks (MHN), outsourced disease detection services demand the privacy preservation of medical users and health service providers (health clouds). This necessitates the use of a fully homomorphic encryption (FHE) while providin
Externí odkaz:
https://doaj.org/article/6feb517f72854596a41824862b53a5d1
The basic framework of the superfluid vortex model for pulsar glitches, though, is well accepted; there is a lack of consensus on the possible trigger mechanism responsible for the simultaneous release of a large number ($\sim 10^{17}$) of superfluid
Externí odkaz:
http://arxiv.org/abs/2411.19060
The growing adoption of machine learning (ML) in modelling atmospheric and oceanic processes offers a promising alternative to traditional numerical methods. It is essential to benchmark the performance of both ML and physics-informed ML (PINN) model
Externí odkaz:
http://arxiv.org/abs/2411.19031
Autor:
Chen, Kai-Feng, Wilensky, Michael J., Liu, Adrian, Dillon, Joshua S., Hewitt, Jacqueline N., Adams, Tyrone, Aguirre, James E., Baartman, Rushelle, Beardsley, Adam P., Berkhout, Lindsay M., Bernardi, Gianni, Billings, Tashalee S., Bowman, Judd D., Bull, Philip, Burba, Jacob, Byrne, Ruby, Carey, Steven, Choudhuri, Samir, Cox, Tyler, DeBoer, David R., Dexter, Matt, Eksteen, Nico, Ely, John, Ewall-Wice, Aaron, Furlanetto, Steven R., Gale-Sides, Kingsley, Garsden, Hugh, Gehlot, Bharat Kumar, Gorce, Adélie, Gorthi, Deepthi, Halday, Ziyaad, Hazelton, Bryna J., Hickish, Jack, Jacobs, Daniel C., Josaitis, Alec, Kern, Nicholas S., Kerrigan, Joshua, Kittiwisit, Piyanat, Kolopanis, Matthew, La Plante, Paul, Lanman, Adam, Ma, Yin-Zhe, MacMahon, David H. E., Malan, Lourence, Malgas, Cresshim, Malgas, Keith, Marero, Bradley, Martinot, Zachary E., McBride, Lisa, Mesinger, Andrei, Mohamed-Hinds, Nicel, Molewa, Mathakane, Morales, Miguel F., Murray, Steven G., Nuwegeld, Hans, Parsons, Aaron R., Pascua, Robert, Qin, Yuxiang, Rath, Eleanor, Razavi-Ghods, Nima, Robnett, James, Santos, Mario G., Sims, Peter, Singh, Saurabh, Storer, Dara, Swarts, Hilton, Tan, Jianrong, van Wyngaarden, Pieter, Zheng, Haoxuan
The precise characterization and mitigation of systematic effects is one of the biggest roadblocks impeding the detection of the fluctuations of cosmological 21cm signals. Missing data in radio cosmological experiments, often due to radio frequency i
Externí odkaz:
http://arxiv.org/abs/2411.10529
Autor:
Hamna, Sudharsan, Deepthi, Seth, Agrima, Budhiraja, Ritvik, Khullar, Deepika, Jain, Vyshak, Bali, Kalika, Vashistha, Aditya, Segal, Sameer
Large Language Models (LLMs) and Text-To-Image (T2I) models have demonstrated the ability to generate compelling text and visual stories. However, their outputs are predominantly aligned with the sensibilities of the Global North, often resulting in
Externí odkaz:
http://arxiv.org/abs/2410.19419
A Scalable Tool For Analyzing Genomic Variants Of Humans Using Knowledge Graphs and Machine Learning
The integration of knowledge graphs and graph machine learning (GML) in genomic data analysis offers several opportunities for understanding complex genetic relationships, especially at the RNA level. We present a comprehensive approach for leveragin
Externí odkaz:
http://arxiv.org/abs/2407.20879
Adverse event (AE) extraction following COVID-19 vaccines from text data is crucial for monitoring and analyzing the safety profiles of immunizations. Traditional deep learning models are adept at learning intricate feature representations and depend
Externí odkaz:
http://arxiv.org/abs/2406.18049
Autor:
Kitching, Christopher R., Kauhanen, Henri, Abbott, Jordan, Gopal, Deepthi, Bermúdez-Otero, Ricardo, Galla, Tobias
In this paper we study networks of nodes characterised by binary traits that change both endogenously and through nearest-neighbour interaction. Our analytical results show that those traits can be ranked according to the noisiness of their transmiss
Externí odkaz:
http://arxiv.org/abs/2405.12023
Autor:
Bera, Chinmay, Deepthi, K. N.
Protvino to ORCA (Oscillation Research with Cosmics in the Abyss) (P2O) is an upcoming neutrino oscillation experiment with a very long baseline of 2595 km. Due to the substantial baseline, this experiment provides a unique opportunity to study the e
Externí odkaz:
http://arxiv.org/abs/2405.03286
Autor:
Maazallahi, Abbas, Thota, Sreehari, Kondaboina, Naga Prasad, Muktineni, Vineetha, Annem, Deepthi, Rokkam, Abhi Stephen, Amini, Mohammad Hossein, Salari, Mohammad Amir, Norouzzadeh, Payam, Snir, Eli, Rahmani, Bahareh
This study analyzes crop yield prediction in India from 1997 to 2020, focusing on various crops and key environmental factors. It aims to predict agricultural yields by utilizing advanced machine learning techniques like Linear Regression, Decision T
Externí odkaz:
http://arxiv.org/abs/2404.15392