1,726,963 research outputs found
Randa-lab/Bayesian_Neural_Network_Probabilistic_Ionosphere_VTEC: Bayesian_Neural_Network_Probabilistic_Ionosphere
Bayesian neural network models for probabilistic VTEC forecasting with 95% confidence, from the paper "Uncertainty Quantification for Machine Learning-based Ionosphere and Space Weather Forecasting" by Natras Randa et al., submitted to the Space Weather Jornal, AGU.
Two Bayesian neural network models were developed for VTEC forecasting with 95% confidence intervals. In both models, the deterministic network parameters (weights) are replaced by probability distributions of these weights. The first model only describes the uncertainty in the weights and estimates the model uncertainty, while the second model also estimate the data uncertainty by providing probabilistic output estimate via minimizing the negative log-likelihood (NLL) loss
Randa-lab/Bayesian_Neural_Network_Probabilistic_Ionosphere_VTEC: Bayesian_Neural_Network_Probabilistic_Ionosphere
Bayesian neural network models for probabilistic VTEC forecasting with 95% confidence, from the paper "Uncertainty Quantification for Machine Learning-based Ionosphere and Space Weather Forecasting" by Natras Randa et al., submitted to the Space Weather Jornal, AGU.
Two Bayesian neural network models were developed for VTEC forecasting with 95% confidence intervals. In both models, the deterministic network parameters (weights) are replaced by probability distributions of these weights. The first model only describes the uncertainty in the weights and estimates the model uncertainty, while the second model also estimate the data uncertainty by providing probabilistic output estimate via minimizing the negative log-likelihood (NLL) loss
Randa-lab/Quantile_Gradient_Boosting_for_Probabilistic_VTEC: Quantile_Gradient_Boosting_Probabilistic_Ionosphere_Evaluation
This release demonstrates how to load and evaluate the probabilistic Quantile Gradient Boosting (QGB) Vertical Total Electron Content (VTEC) models, which provide 95% confidence intervals. QGB VTEC models forecast VTEC 1-day ahead for grid points at 10° of longitude, and 10°, 40°, and 70° of latitude. They were developed within the study "Uncertainty Quantification for Machine Learning-based Ionosphere and Space Weather Forecasting" by Natras R., Soja B. and Schmidt M., submitted to the Space Weather Jornal, AGU.
Quantiles were estimated by multiplying the quantile values β by the positive and negative residuals in the loss function to obtain the quantile loss (QL) (see Equation 7 in the paper). Quantile values of β ={0.025, 0.975} are chosen for estimating the lower and upper confidence bounds, respectively, to obtain a confidence interval of 95%. The mean quantile β={0.50} provides the median VTEC
Introducing our Publications and Editorial Board: Randa Al Chidiac
Randa Al Chidiac is the Executive Director of the Library at the Holy Spirit University of Kaslik (USEK), Lebanon. Randa has been in the University since 2012, where she is responsible for the strategic planning, management and administration of library resources and services, as well as the Centre for Written Heritage Conservation and the Centre for Reprography and Digitization. Prior to this position, she was the E-Resources Librarian at the University of Balamand, Lebanon
Oral history interview with Randa Parrish
Randa Parrish, owner of Prairie Quilt Shop in Hennessey, Oklahoma, recalls her decision to buy a fabric store in 2001 and some of the challenges she faced along the way. She shares some of her marketing successes from "strip club" events and retreats to shop hops. Parrish discusses the impact of the COVID-19 pandemic had on revenue, the supply chain, and branching out to take advantage of online opportunities. She describes her staff learning how to make videos to upload to Facebook, introducing an app, and how customers in the shop have declined due to the pandemic. She explains the process of designing fabric, where she gets some of her inspiration, and the ways her team contributes to the enterprise.The COVID-19 in Oklahoma Collection is a series of interviews which document how Oklahomans were affected by the global COVID-19 pandemic. This project was made possible with support from the Institute for Museums and Library Services American Rescue Plan Grant
RANDA BENGSRAT: EMANSIPASI, CINTA, DAN KEIMANAN
Dalam cerita-cerita tentang wanita, ditemukan citra wanita sesuai dengan sudut pandang pengarangnya. Citra wanita pertama ialah yang bertingkah baik yang menampilkan sifat penurut dan berbakti kepada orang lain. Citra wanita kedua ialah wanita yang dapat mengekspresikan diri melawan dominasi pria. Salah satu roman yang menceritakan kehidupan wanita ialah Randa Bengsrat ‘Janda Utuh’. Randa Bengsrat merupakan roman Sunda karya Jus Rusamsi. Randa Bengsrat adalah sebuah roman (modern) yang cukup menarik dan mengesankan untuk bacaan generasi muda. Randa Bengsrat banyak membahas masalah-masalah aktual bertalian dengan perjuangan kaum wanita untuk menempatkan dirinya dalam masyarakat di Negara sedang berkembang yang bersifat majemuk, seperti Indonesia
Randa\u27s Camera Store
Randa\u27s Camera Storehttps://mavmatrix.uta.edu/specialcollections_wdsmithphotography/3237/thumbnail.jp
RANDA BENGSRAT: EMANSIPASI, CINTA, DAN KEIMANAN
Dalam cerita-cerita tentang wanita, ditemukan citra wanita sesuai dengan sudut pandang pengarangnya. Citra wanita pertama ialah yang bertingkah baik yang menampilkan sifat penurut dan berbakti kepada orang lain. Citra wanita kedua ialah wanita yang dapat mengekspresikan diri melawan dominasi pria. Salah satu roman yang menceritakan kehidupan wanita ialah Randa Bengsrat ‘Janda Utuh’. Randa Bengsrat merupakan roman Sunda karya Jus Rusamsi. Randa Bengsrat adalah sebuah roman (modern) yang cukup menarik dan mengesankan untuk bacaan generasi muda. Randa Bengsrat banyak membahas masalah-masalah aktual bertalian dengan perjuangan kaum wanita untuk menempatkan dirinya dalam masyarakat di Negara sedang berkembang yang bersifat majemuk, seperti Indonesia.</jats:p
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