-
[Adversarial Robustness of Graph Neural Networks](https://mediatum.ub.tum.de/1641938)
```bib
@phdthesis{zugner2022adversarial,
title={Adversarial Robustness of Graph Neural Networks},
author={…
-
[𝑝-Laplacian Based Graph Neural Networks](https://proceedings.mlr.press/v162/fu22e.html)
```bib
@inproceedings{fu2022p,
title={$ p $-Laplacian Based Graph Neural Networks},
author={Fu, Guoji a…
-
[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…
-
Graph neural networks are a popular choice for forecasting hierarchically structured panels, graph structured panels, or structured variable settings, e.g., energy networks with time series observed a…
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[Graph neural networks with diverse spectral filtering](https://dl.acm.org/doi/abs/10.1145/3543507.3583324)
```bib
@inproceedings{guo2023graph,
title={Graph neural networks with diverse spectral …
-
[Spectral adversarial training for robust graph neural network](https://ieeexplore.ieee.org/abstract/document/9950609/)
```bib
@article{li2022spectral,
title={Spectral adversarial training for ro…
-
[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…
-
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…
-
https://arxiv.org/abs/2409.19096
```bib
@article{sirohi2024enhancing,
title={Enhancing Robustness of Graph Neural Networks through p-Laplacian},
author={Sirohi, Anuj Kumar and Halder, Subhanu …
-
## 레퍼런스 논문
1. Graph Clustering with Graph Neural Networks (DMoN)
- paper : [https://arxiv.org/abs/2006.16904](https://arxiv.org/abs/2006.16904)
- code : [https://github.com/google-research/go…