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Hello, GPT2 has positional encoding module, thus only a linear projection is used to project the input time series to the required dimension., but DataEmbedding (TokenEmbedding + PositionalEmbedding +…
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Issue: ReX can only handle datasets in which there is identical number of replicates across timepoints (perhaps across states also?).
This may be quite a common issue as there can be missed timepo…
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I executed the code for model 15.5 from the book (for doing missing data imputation with primate milk data.
The model runs fine but when I try to sample from posterior distribution using sim() functi…
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## Description of your problem
Using the imputation feature leads to an automatic split-up of the model variables.
In the `pm.model_to_graphviz` visualization that causes arrows to go in the rever…
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Currently, `brms` drops the censored data for most `pp_check` types. A better approach would be to impute the observations. See a `bayesplot` issue https://github.com/stan-dev/bayesplot/issues/319 for…
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Since you mentioned you're considering enhancing load_data(), I might also try to expose to the user different methods for imputation of missing numeric data. Currently in data_utils.load_num_feats() …
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Good morning,
Asking once more for your input on deploying Higashi!
I have set up a test run that I could efficiently run locally on my NVidia GPU (chr21, 1mln bp windows). Everything works on my la…
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@GaelVaroquaux points out that iterative imputation with a regularised least-squares model is more-or-less the same as using NMF for imputation. We should instead use RandomForestRegressor as the defa…
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The algorithm listed as `GeneralImputer` here is more widely-known as MICE (Multiple imputation by chained equations) in statistics. I'm not sure if the name used here is standard in ML, but the lack …