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State space models are applied broadly across fields including computer science, statistics and engineering, using a wide array of methods for their estimation and inference. Despite the plethora of t…
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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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Consider the following resources for machine learning, probability, and classic AI
## tagged machine learning
[Wheel/Rail Adhesion State Identification of Heavy-Haul Locomotive Based on Particle…
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Visualise the interactions of variables within the system.
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Hi Daniel,
I've finally managed to create a visualization for Bayesian Networks constructed from Categoricals.
Check out the README of the Gist here:
https://gist.github.com/nightscape/c2fcccac859b3a…
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### Subject of the issue
It seems that a Bayesian network predicts equal probabilities for all possible outcomes in unseen scenarios. This confuses me, and I wonder if I have misunderstood the algori…
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Hi, I'm totally new to these kinds of networks.
Can anybody help me with hyperparameter tuning for a specific architecture(e.g. unet) ?
for example changing activation functions, num of filters …
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Dear Zachary,
I hope all is well.
I wanted to inquire about your pre-print and the beta/rank penalty parameter tuning for model selection.
Specifically in your manuscript, you've written :
…
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Hi, team!
I'm interested in it but it's hard to get it.
I have some questions about wide networks.
1) What's the prediction of wide networks, e.g., NNGP? Evaluated mean of GP? Is it deterministic? If …