High-redshift cosmological data remain consistent with the standard distance duality relation within roughly 2 sigma when distances are reconstructed model-independently with an artificial neural network.
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2 Pith papers cite this work. Polarity classification is still indexing.
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SuperLearner model estimates peak energies of Swift GRBs with average Pearson r=0.72 in cross-validation and produces values for 650 additional bursts.
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Testing the Distance Duality Relation with Cosmological Observations at high Redshift using Artificial Neural Network
High-redshift cosmological data remain consistent with the standard distance duality relation within roughly 2 sigma when distances are reconstructed model-independently with an artificial neural network.
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Estimating the peak energy of Swift gamma-ray bursts using supervised machine learning
SuperLearner model estimates peak energies of Swift GRBs with average Pearson r=0.72 in cross-validation and produces values for 650 additional bursts.