Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles
<jats:p>The inaccuracy of neural network models on inputs that do not stem from the distribution underlying the training data is problematic and at times unrecognized. Uncertainty estimates of model predictions are often based on the variation in predictions produced by a diverse ensemble of m...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Association for the Advancement of Artificial Intelligence (AAAI)
2022
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| Online Access: | https://hdl.handle.net/1721.1/143573 |