Comments (4)
I would have assumed this to give the same result, since the theoretical solution is exactly the same, since the model is linear (thus the linearization does not depend on m).
from bayem.
Even if you decrease the tolerance such that it is never reached and VB iterates 50 times -- and I would expect 50 fixed-point iterations to be enough -- you get the same result as above...
from bayem.
That could be checked with the analytical example, we could take 2 data points and compute the exact solution with a given prior, and then do the same thing with the sequential approach. Would Isabela or Abbas being interested to check the standard deviation part in the example for the analytical solution Thomas implemented and verify, if this is true for the subsequent iteration, and then, why this is not the case for our implementation. Maybe we still have a bug in our implementation that leads to wrong results, and then any discussion of results with a larger complexity might be obsolete.
from bayem.
If I skip the noise update (I know that this actually requires a new derivation of the equations...), the parameter posteriors match. So I also expect investigating the standard deviation part in the example for the analytical solution to be fruitful.
from bayem.
Related Issues (20)
- Remove sphinx from requirements HOT 2
- Proper VB scaling HOT 2
- Potential bug in our F formula HOT 6
- Prescribed correlation (in noise model) HOT 28
- Remove Gamma.Noninformative()? HOT 1
- Linearity check HOT 3
- Towards `bayem` HOT 6
- Failing visualization test
- Fancy readme
- Docstrings
- pre-commit hooks
- Check ARD implementation HOT 1
- VB `state` variable HOT 1
- VB_postprocess_per_iteration HOT 4
- VB_handle_diverging_ME HOT 4
- Sub-optimal control flow HOT 1
- Visualization of marginalized posteriors HOT 3
- Changes in visualization somehow break the CI HOT 1
- levels are not always computed correctly
- remove python 3.7
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from bayem.