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Improving Deep Ensembles for Better Deep Uncertainty Quantification
https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/improving_deep_ensembles.pdf15 Nov 2021: However, theextrapolations away from training samples, produced by models with these parameter sets candiffer greatly. ... The first dataset examined, chosen for popularity andfast experimentation, is MNIST (LeCun et al., 2010). -
Depth Uncertainty Networks for Active Learning
https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/depth_uncertainty_networks_for_active_learning_reduced.pdf15 Nov 2021: Finally,we propose a modification to an information-based acquisition strategy, termed truncatedBALD, which mitigates bias caused by model misspecification. ... Bayesian deep learning provides a solution to the first two of these issues.
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