Eirik Østmo / Torger Grytå

VI seminar #49 – Quantify Predictive Uncertainty for a Pretrained Network

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Quantify Predictive Uncertainty for a Pretrained Network 

Presenter:  Edward Fabian Meyer Bull, Visual intelligence PhD student at UiO


Edward Fabian Bull (photo: private)

To trust the predictions provided by deep neural networks we need to quantify the uncertainty. This can be done with Bayesian neural networks. But how can we quantify uncertainty for an already trained network?

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