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If I understand correctly, the objective in this work is to select a coreset such that the likelihood over the parameters of the model is as close as possible to the likelihood over the parameters for…
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I mentioned this in an email but I wanted to give you a concrete example. [Pyro](http://pyro.ai/) is a probabilistic programming language built on top of PyTorch that has stochastic variational infere…
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First of all, really great job! I skimmed through the provided examples and so far I was only able to find examples which seem to run the algorithm from scratch. At least that's how I understand the b…
pmayd updated
5 years ago
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There is only one notebook example, SVI.ipynb, of stochastic variational inference. In this example, X = input, Y = multiple outputs (2 columns Y1 and Y2) and Z = inducing variables.
Z = np. random.…
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We're seeing a rather large amount of variance in the value of MLL with an ExactGP obtained while holding the model and data fixed. Here is a repro case in which we get changes in MLL up to 30% across…
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Hi, is there any plan to support [Automatic Differentiation Variational Inference](http://arxiv.org/abs/1603.00788)?
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Hi Mike,
Any plans to include the ability to create models with priors and distributions?
Then inference would have to include facilities to sample from the posterior like MCMC, Variational me…
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When I try to run the example code in the readme, bar the second and third training calls, like:
```python
import pandas as pd, numpy as np
from hpfrec import HPF
## Generating sample counts d…
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Hello,
Great package. I have some questions if anyone has a second.
1. Is there a posterior predictive check method?
2. Can the random variables be used in any arbitrary julia function?
3. A…
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