Efficient data acquisition and training of collisional-radiative model artificial neural network surrogates through adaptive parameter space sampling

Overview of attention for article published in Machine Learning: Science and Technology, October 2022

Altmetric Badge

About this Attention Score

Average Attention Score compared to outputs of the same age

Mentioned by

twitter: 3 X users

Readers on

mendeley: 10 Mendeley

So far, Altmetric has seen 4 X posts from 3 X users, with an upper bound of 11,845 followers.

RT @MLSTjournal: 'Efficient #data acquisition and training of collisional-radiative model artificial #neuralnetwork...' by P Balaprakash @n…

'Efficient #data acquisition and training of collisional-radiative model artificial #neuralnetwork...' by P Balaprakash @n8Sci @MaulikRomit et al @Griffith_Uni @LosAlamosNatLab @argonne @argonne_lcf hits 500 downloads! https://t.co/S5vq6zn2vO #machinele…

RT @MLSTjournal: Great new work by P Balaprakash @n8Sci @MaulikRomit et al @Griffith_Uni @LosAlamosNatLab @argonne @argonne_lcf - 'Efficien…

Great new work by P Balaprakash @n8Sci @MaulikRomit et al @Griffith_Uni @LosAlamosNatLab @argonne @argonne_lcf - 'Efficient #data acquisition and training of collisional-radiative model artificial #neuralnetwork...' - https://t.co/S5vq6zn2vO #machinelea…

This page shows the most recent X posts that mention this research output. Click here to find out how to access more activity.

Login to access the Sentiment Analysis related to this output.