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I am working with the LinearGaussianSSM with time varying emission weights based on the example in Online linear regression using Kalman filtering. I found problems with 1) setting model parameters and sampling data which generates samples with wrong emission dimensions; 2) performing inference with EM, when we freeze emission weights (Trainable==False) to given time-varying values, the model still learns them but with the wrong dimension; 3) fit_sgd gives error messages. I illustrated these issues in this notebook.
The text was updated successfully, but these errors were encountered:
I am working with the LinearGaussianSSM with time varying emission weights based on the example in Online linear regression using Kalman filtering. I found problems with 1) setting model parameters and sampling data which generates samples with wrong emission dimensions; 2) performing inference with EM, when we freeze emission weights (Trainable==False) to given time-varying values, the model still learns them but with the wrong dimension; 3) fit_sgd gives error messages. I illustrated these issues in this notebook.
The text was updated successfully, but these errors were encountered: