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The challenge is that we need to keep the sampled per-LV-layer losses (local KLs), not summing them up as is the default. This probably means we'll have to write a custom Model subclass that has a train_step() that handles the custom IWVI objective...
The text was updated successfully, but these errors were encountered:
We'd like GPflux to be able to implement importance-weighting as in https://github.com/hughsalimbeni/DGPs_with_IWVI/.
The challenge is that we need to keep the sampled per-LV-layer losses (local KLs), not summing them up as is the default. This probably means we'll have to write a custom Model subclass that has a train_step() that handles the custom IWVI objective...
The text was updated successfully, but these errors were encountered: