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Hi! I would like to use bayespy in my diploma thesis. It seems more advanced than other libraries available. On the other hand, I spent most of this day reading the documentation trying to figure out …
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[ICML 2023 Workshop SPIGM homepage](https://openreview.net/group?id=ICML.cc/2023/Workshop/SPIGM)
```bib
@inproceedings{
wang-henderson2023graph,
title={Graph Neural Network Powered Bayesian Opt…
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Pose a question about one of the following articles:
“[Deep neural networks are more accurate than humans at detecting sexual orientation from facial images](https://psycnet.apa.org/doiLanding?doi…
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Maximizing the expected log posterior density (ELPD) is a common objective function in Bayesian inference and Bayesian neural networks, and I'd be interested in having it as a loss function for a pack…
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The current method of storing all nonzero outcomes simply won't scale. We'll need to implement a distribution based on Bayesian networks, queries via belief propagation.
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This is really an exploratory question about implementing a Bayesian layer in Equinox. My research requires Bayesian neural networks, and I've been playing with Equinox to see how it stacks up to Flax…
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Hi,
I'm currently trying to build a hybrid Bayesian Network with continuous and discrete variables and learn the parameters from data.
The model structure is looking like this:
 that can be interesting for Lasagne users. It links PyMC3 and Lasagne for constructing neural networks from bayesi…
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I ran ``coverage run --source=robo -m unittest discover test -v`` and got
```
======================================================================
ERROR: test_bayesian_optimization (test_fmin.t…
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### Issue Description
Currently training some bayesian neural networks using HMC, would it be useful to include the calculation of log likelihood as a helper function? probably something like this u…