Zobrazeno 1 - 10 of 1 090 pro vyhledávání: '"Hernandez, Diego A."'
1
Report
Neural network emulator to constrain the high-$z$ IGM thermal state from Lyman-$\alpha$ forest flux auto-correlation function
Autor: Jin, Zhenyu, Wolfson, Molly, Hennawi, Joseph F., González-Hernández, Diego
We present a neural network emulator to constrain the thermal parameters of the intergalactic medium (IGM) at $\displaystyle{5.4}\le{z}\le{6.0}$ using the Lyman-$\displaystyle\alpha$ (Ly$\displaystyle\alpha$) forest flux auto-correlation function. Ou
Externí odkaz: http://arxiv.org/abs/2410.06505
Zobrazit plný text záznamu
2
Report
Multi-machine preventative maintenance scheduling with imperfect interventions: a restless bandit approach
Autor: Ruiz-Hernandez, Diego, Pinar-Pérez, Jesús María, Delgado-Gómez, David
Publikováno v: Computers & Operations research. Volume 119, 104927 (2020)
In this paper we address the problem of allocating the efforts of a collection of repairmen to a number of deteriorating machines in order to reduce operation costs and to mitigate the cost (and likelihood) of unexpected failures. Notwithstanding the
Externí odkaz: http://arxiv.org/abs/2401.14055
Zobrazit plný text záznamu
5
Report
A Real Use Case of Semi-Supervised Learning for Mammogram Classification in a Local Clinic of Costa Rica
Autor: Calderon-Ramirez, Saul, Murillo-Hernandez, Diego, Rojas-Salazar, Kevin, Elizondo, David, Yang, Shengxiang, Molina-Cabello, Miguel
The implementation of deep learning based computer aided diagnosis systems for the classification of mammogram images can help in improving the accuracy, reliability, and cost of diagnosing patients. However, training a deep learning model requires a
Externí odkaz: http://arxiv.org/abs/2107.11696
Zobrazit plný text záznamu
10
Report
Partition Quantitative Assessment (PQA): A quantitative methodology to assess the embedded noise in clustered omics and systems biology data
Autor: Camacho-Hernández, Diego A., Nieto-Caballero, Victor E., León-Burguete, José E., Freyre-González, Julio A.
Identifying groups that share common features among datasets through clustering analysis is a typical problem in many fields of science, particularly in post-omics and systems biology research. In respect of this, quantifying how a measure can cluste
Externí odkaz: http://arxiv.org/abs/2101.03228
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje