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Trained CIFAR10 models and predictions for label shift experiments

appsOther research productkeyboard_double_arrow_right Other ORP type 21 Apr 2019Publisher:Zenodo
Authors: Shrikumar, Avanti;

doi: 10.5281/zenodo.3458525 , 10.5281/zenodo.3412990 , 10.5281/zenodo.3406662 , 10.5281/zenodo.3458206 , 10.5281/zenodo.2648107

Trained CIFAR10 models and predictions for label shift experiments

Abstract

Trained CIFAR10 models and predictions for label shift experiments. Models trained with https://github.com/kundajelab/uncertainty_experiments/blob/bb16abb6cbb04877fa8b1a821a80ce8f5723b0d9/cifar10/Train%20model.ipynb, predictions with https://github.com/kundajelab/label_shift_experiments/blob/master/cifar10/Download_CIFAR10_models_from_zenodo_and_make_predictions.ipynb

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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