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[Spectral adversarial training for robust graph neural network](https://ieeexplore.ieee.org/abstract/document/9950609/)
```bib
@article{li2022spectral,
title={Spectral adversarial training for ro…
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[Robust graph neural networks using weighted graph laplacian](https://arxiv.org/abs/2208.01853)
```bib
@article{runwal2022robust,
title={Robust graph neural networks using weighted graph laplac…
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### Type of Edit (select all that apply)
Add new content (definitions, codeblocks, etc.)
### Description (optional)
We would like to edit the `Convolutional Neural Networks` concept entry under AI.…
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1. **Grokking Deep Learning**
https://edu.anarcho-copy.org/Algorithm/grokking-deep-learning.pdf
2. **Deep Learning - Uczenie głębokie z językiem Python. Sztuczna inteligencja i sieci neuronowe**
P…
Eteiz updated
1 month ago
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[Strategies for pre-training graph neural networks](https://arxiv.org/abs/1905.12265)
```bib
@article{hu2019strategies,
title={Strategies for pre-training graph neural networks},
author={Hu, W…
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Hello. Interesting work, but I am having trouble reproducing your results.
The code from example notebook:
```
_markov_chain = MarkovChain(
[[0.3, 0.5, 0.2],
[0.1, 0.8, 0.1], …
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Self-Compressing Neural Networks is dynamic quantization-aware training that puts the size of the model in the loss
Paper: https://arxiv.org/pdf/2301.13142
Code: https://github.com/geohot/ai-noteb…
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### Feature description
Radial Basis Function Neural Networks (RBFNNs) are a type of neural network that combines elements of clustering and function approximation, making them powerful for both regr…
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Greetings Patrick,
I was wondering, what are your thoughts when it comes to Graph Neural Networks? Would a GNNlayer be implemented as a module for Equinox or an advanced example for the documentati…
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https://arxiv.org/pdf/1906.01629
```bib
@misc{gasse2019exactcombinatorialoptimizationgraph,
title={Exact Combinatorial Optimization with Graph Convolutional Neural Networks},
author…