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### This issue reports the results of my SuperLoss hyperparameter study on IMDB and DBLP.
You can find results in detail [here](https://docs.google.com/spreadsheets/d/1oatYd2uMXOah8RQJsvaT2NIwxhh6C…
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Hi There,
What would be the best way to access the mean and the covariance of the variational posterior distribution in the **bayesian_neural_network.py** example?
Everything is happening under …
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I am having problems to understand deterministic Var Ratios and deterministic BALD acquisition functions... For example, in deterministic BALD, since the neural network is deterministic, is not the mu…
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I am using the **DenseFlipOut** layer, I see that it has a mean_normal distribution over the weights and the biases by default, but I was wondering how these distributions are modified during training…
pks42 updated
9 months ago
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Hello,
I am trying to figure out if there is a way to get the shelfnet network also give the confidence of the segmented class during test time.Basically give how accurate the network thinks the segm…
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The current dynamical systems tutorial notebook in #241 is quite long. Maybe it would be easier to digest if it were broken up into 2-3 smaller tutorials covering different segments of the existing co…
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**Describe the bug**
Hi, thanks for the excellent library. I have been using the library for a while now and have found that whenever I'm dealing with fitting `GaussianProcessRegression` models Tenso…
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We are trying to reproduce the results presented in the paper "![What Are Bayesian Neural Network Posteriors Really Like?](https://arxiv.org/abs/2104.14421)". However, when we tried to run the script,…
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This outlines a roadmap for basic statistical functionality that Julia needs to offer. It is heavily drawn from the table of contents for MASS.
- [ ] Data processing [DataFrames.jl](https://github.com…