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I’ve been reading through the deep review paper and noticed that there is not a Methylation section in this paper. There are a number of issues that have been brought up regarding the inclusion of met…
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Would there be any interest in having a class of distance metrics for Probability Distributions?
An example could be like the very-pseduo code in [this jupyter notebook](https://github.com/bhargavvad…
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I'm trying to use GPyTorch for COVID-19 prediction by training a deep GP. Let's say I'm trying to predict daily deaths in C counties for the next N days, and I have the following time series as predi…
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Please add some more examples on doing variational inference in tensorflow probability, including ADVI and BBVI.
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The idea is simple to implement and well-scoped as part of TF Distributions. I personally like the idea of even having it be the default for Gamma, Beta, and others. The gradient implementations may b…
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Hi there,
I wonder how to pass all tests.
That is the output
### Test Summary: | Pass Error Total
#### Turing …
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**System information**
- Have I written custom code (as opposed to using a stock example script provided in TensorFlow): yes
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 18.04
…
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Hi,
In the example notebook for Contextual Topic Modeling, we can get topic distribution for a document via
`distribution = ctm.get_thetas(training_dataset)[8] # topic distribution for the first do…
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https://turing.ml/dev/tutorials/9-variationalinference
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In the tutorials you give in this repo, many of them only involve one cycle of BO: sample some data and then optimize the acquisition function and then get the best point. But in reality, BO should in…