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This is the part 1 of Understanding weight matrices and parameters count of different deep learning ensemble models used for Uncertainty Estimation - Deep Ensemble, Batch Ensemble & Rank-1 BNN.
In this video we are not going to cover in depth about the uncertainty estimation or the ensemble approaches. We will see for the three approaches
* On a high level how the weight matrices are defined
* Code a simple MLP for deep ensemble , batch ensemble and rank-1 BNN
* Compute the parameters for all the above
* then convince us mathematically about the number of parameters in each of this paper make sense
* and show the comparison through graph
GitHub Repo: github.com/anujshah1003/uncer...