Zobrazeno 1 - 10
of 49 304
pro vyhledávání: '"Ong P"'
Publikováno v:
Journal of Asthma and Allergy, Vol Volume 15, Pp 1681-1700 (2022)
Albert C Chong,1 Kittipos Visitsunthorn,2 Peck Y Ong1– 3 1Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; 2Department of Pediatrics, Children’s Hospital Los Angeles, Los Angeles, CA, USA; 3Division of Clinical Im
Externí odkaz:
https://doaj.org/article/dcbb1bf862484c27b52f9cd0b18de1db
Publikováno v:
International Medical Case Reports Journal, Vol Volume 15, Pp 599-603 (2022)
Fathul Huda,1,2 Paulus Anam Ong,2 Yusuf Wibisono,2 Sofiati Dian,2 Ahmad Rizal Ganiem2 1Department of Biomedical Sciences, Faculty of Medicine, Universitas Padjadjaran, Bandung, West Java, Indonesia; 2Department of Neurology, Faculty of Medicine, Univ
Externí odkaz:
https://doaj.org/article/049584ed613a49c8b96c82e2b41051fd
Autor:
Nguyen, Hiep, Tang, Haiyang, Alger, Matthew, Marchal, Antoine, Muller, Eric G. M., Ong, Cheng Soon, McClure-Griffiths, N. M.
Publikováno v:
MNRAS 2024
We introduce TPCNet, a neural network predictor that combines Convolutional and Transformer architectures with Positional encodings, for neutral atomic hydrogen (HI) spectral analysis. Trained on synthetic datasets, our models predict cold neutral ga
Externí odkaz:
http://arxiv.org/abs/2411.13325
Few-Shot Learning (FSL) is a challenging task, which aims to recognize novel classes with few examples. Pre-training based methods effectively tackle the problem by pre-training a feature extractor and then performing class prediction via a cosine cl
Externí odkaz:
http://arxiv.org/abs/2411.12259
Language Model Evolutionary Algorithms for Recommender Systems: Benchmarks and Algorithm Comparisons
In the evolutionary computing community, the remarkable language-handling capabilities and reasoning power of large language models (LLMs) have significantly enhanced the functionality of evolutionary algorithms (EAs), enabling them to tackle optimiz
Externí odkaz:
http://arxiv.org/abs/2411.10697
We study the problem of bounding the posterior distribution of discrete probabilistic programs with unbounded support, loops, and conditioning. Loops pose the main difficulty in this setting: even if exact Bayesian inference is possible, the state of
Externí odkaz:
http://arxiv.org/abs/2411.10393
Autor:
Wu, Sanfeng, Schoop, Leslie M., Sodemann, Inti, Moessner, Roderich, Cava, Robert J., Ong, N. P.
Publikováno v:
Nature (2024) 635 301-310
Experiments on quantum materials have uncovered many interesting quantum phases ranging from superconductivity to a variety of topological quantum matter including the recently observed fractional quantum anomalous Hall insulators. The findings have
Externí odkaz:
http://arxiv.org/abs/2411.09496
Autor:
Lauer-Coles, A., Deibel, C. M., Blackmon, J. C., Hood, A., Good, E. C., Macon, K. T., Santiago-Gonzalez, D., Schatz, H., Ahn, T., Browne, J., Montes, F., Schmidt, K., Ong, 4 W. J., Chipps, K. A., Pain, S. D., Wiedenhöver, I., Baby, L. T., Rijal, N., Anastasiou, M., Upadhyayula, S., Bedoor, S., Hooker, J., Koshchiy, E., Rogachev, G. V.
Background: Type I X-Ray bursts (XRBs) are energetic stellar explosions that occur on the surface of a neutron star in an accreting binary system with a low-mass H/He-rich companion. The rate of the $^{34}$Ar($\alpha,p$)$^{37}$K reaction may influenc
Externí odkaz:
http://arxiv.org/abs/2411.09918
Molecular docking enables virtual screening of compound libraries to identify potential ligands that target proteins of interest, a crucial step in drug development; however, as the size of the compound library increases, the computational complexity
Externí odkaz:
http://arxiv.org/abs/2411.06740
Despite remarkable achievements in deep learning across various domains, its inherent vulnerability to adversarial examples still remains a critical concern for practical deployment. Adversarial training has emerged as one of the most effective defen
Externí odkaz:
http://arxiv.org/abs/2411.02871