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https://arxiv.org/pdf/2207.08200
this paper provides a different way to optimize the priors using distance aware priors.
Maybe i can try to implement it.
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### Issue Type
Bug
### Source
binary
### Keras Version
2.16.0
### Custom Code
No
### OS Platform and Distribution
Linux Ubuntu 20.04
### Python version
3.10
### GPU model and memory
_No r…
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Work with multi-layer bayesian neural networks and compare it with more classical methods (ADVI).
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I think that Bayesian neural networks would be a natural successor to our tutorials on Bayesian GLMs.
As far as the neural network library to use, I think [Flux](https://github.com/FluxML/Flux.jl) …
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**Notebook title**: Variational Inference: Bayesian Neural Networks
**Notebook url**: https://www.pymc.io/projects/examples/en/latest/variational_inference/bayesian_neural_network_advi.html
## Iss…
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Suggested list of courses would be:
- An introduction to deep learning **
- How to train a neural network
- Regularisation in neural networks
- Deep Bayesian neural networks
- Conv…
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See: https://arxiv.org/pdf/1502.05700.pdf
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> [!NOTE]
> If you have a request to support a specific method, or would like to see priority of one of the listed methods, please open a separate issue, so it won't get buried in this thread. Base…
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各位同学好，期中考试的考试范围应当是到11.20日（包括11.20日课，即考试前最后一次课；上一个issue中表述有误）。不包括representation theorem与Neural Networks and Backpropagation的内容。
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The paper "Likelihood-free parameter estimation with neural Bayes estimators" (Sainsbury-Dale, Zammit-Mangion, & Huser, 2023) enables neural amortized *point* estimation, which is generally faster tha…