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Fix for new GPflow heteroskedastic likelihood breaks for quadrature dependent likelihoods #87

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SebastianPopescu opened this issue Nov 22, 2022 · 0 comments
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@SebastianPopescu
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In #84 there were several changes made to accommodate the new framework in GPflow for heteroskedastic likelihoods. More precisely, no_X = None in gpflux/layers/likelihood_layer.py.

This works well with Gaussian or Student-t likelihoods, however it will break when using Softmax, which uses quadrature for variational_expectations or predict_mean_and_var. Both methods require access to the shape of X, so because currently we are passing None this results in an error.

@SebastianPopescu SebastianPopescu added the bug Something isn't working label Nov 22, 2022
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