Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Vipul Arora"'
Publikováno v:
Indian Journal of Radiology and Imaging, Vol 19, Iss 04, Pp 298-300 (2009)
Colobomatous cyst of the orbit is a rare congenital cystic malformation associated with ocular maldevelopment. Usually, the cyst is associated with a microphthalmic globe. We present a rare case of a unilateral large colobomatous cyst associated with
Externí odkaz:
https://doaj.org/article/17cc35d5095e41b089acfe790ab20937
Publikováno v:
SciPost Physics, Vol 16, Iss 5, p 132 (2024)
Deep generative models complement Markov-chain-Monte-Carlo methods for efficiently sampling from high-dimensional distributions. Among these methods, explicit generators, such as Normalising Flows (NFs), in combination with the Metropolis Hastings al
Externí odkaz:
https://doaj.org/article/ff46537f9bba4f638318f969d1d8b9fe
Publikováno v:
SciPost Physics Core, Vol 5, Iss 4, p 052 (2022)
In lattice field theory, Monte Carlo simulation algorithms get highly affected by critical slowing down in the critical region, where autocorrelation time increases rapidly. Hence the cost of generation of lattice configurations near the critical reg
Externí odkaz:
https://doaj.org/article/2506575af98143248109af49df6900b5
Autor:
Akshay Raina, Vipul Arora
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Autor:
Kalpit Yadav, Vipul Arora, Mohit Kumar, Sachchida Nand Tripathi, Vidyanand Motiram Motghare, Karansingh A. Rajput
Publikováno v:
IEEE Sensors Letters. 6:1-4
Autor:
Vansh Bansal, T Thishyan Raj, Nagarathna Ravi, Shubham Korde, Jaskaran Kalra, Sudha Murugesan, B Ramkrishnan, Aboli Gore, Vipul Arora
Publikováno v:
2023 National Conference on Communications (NCC).
Publikováno v:
Physical Review
The traditional Markov chain Monte Carlo (MCMC) suffers from the problem of critical slowing down. Generative machine learning methods, such as normalizing flows, offer a promising method to speed up MCMC simulations, especially in critical regions o
Autor:
Kavya Ranjan Saxena, Vipul Arora
Publikováno v:
Proceedings of the 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD).
Publikováno v:
Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA) ISBN: 9781611977554
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71eaa4edbd480dfd4ba128dc80d0b439
https://doi.org/10.1137/1.9781611977554.ch31
https://doi.org/10.1137/1.9781611977554.ch31
Publikováno v:
IEEE Transactions on Systems, Man, and Cybernetics: Systems. 52:101-111
Passive electroencephalogram (EEG) brain-computer interfaces (BCI) have common usage in the area of Driver Drowsiness Detection. The approach presented herein identifies the cognitive state of the user while no mental action is required. Data recorde