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Hi,
I've had a handful of issues trying to run the mixture gaussians and the bayesian linear regression examples. For reference, I installed tensorflow through anaconda using a separate environment.…
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I am trying to implement variational inference for linear combinations of mixtures of Gaussians in the flavor of
Attias, H. "Independent Factor Analysis." Neural Computation 11.4 (1999): 803-851.
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The input for labels needs to be more clear as to what it's looking for. Currently I have
modelWave = HiddenMarkovModel('Gestures').from_samples(NormalDistribution, 3, training, labels=[sw…
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I'm having trouble fitting simple Gaussian mixture models in PyMC3. On only 500 data points, default inference (NUTS with advi) takes 3-4 minutes. Metropolis inference doesn't seem to work well on thi…
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This is mostly with regard to the changes in #344. The example scripts haven't been rewritten to reflect this, and this should be done.
Also, for example, the examples are sometimes broken - in `ex…
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@ankurankan @khalibartan
I need to construct a Bayesian network to performance inference on non-Gaussian continuous distributions. Looks like the current implementation doesn't support that. What's…
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# Models
We would simulate the following models
### ZINB
Parameters we want to vary are
1. W with K = 1, 2, and 3. Our first idea was to simulate W from a mixture of Gaussians. But, it is…
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In order to use IHM format as a working format while a modeling project is in progress, the externally linked files (comparative models, sequence alignments, EM maps, ensembles of result structures, l…
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Hi there! Thanks for your contribution with Edward!
We are trying to implement a Mixture Gaussian version without marginalizing the local variables (_Cn_)
using _MFVI_ approximation. For this purpos…
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Now, I don't know how the flight modelling handles carburettor icing, or is it up to the aircraft modeller to do some "tricks" on the systems to model it?
Some food for our thoughts:
- http://www.sky…