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同学你好，非常感谢你对这一系列论文的整理和梳理，真的帮助很大！在阅读文献时注意到，仓库中部分标注为“2024-NeurIPS”的论文是“2023-NeurIPS”。以下是我发现的相关论文列表，供参考：
2023-NeurIPS：[Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularizatio…
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[Adversarial Robustness of Graph Neural Networks](https://mediatum.ub.tum.de/1641938)
```bib
@phdthesis{zugner2022adversarial,
title={Adversarial Robustness of Graph Neural Networks},
author={…
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Hi! Why not use adversarial loss？
l-cr updated
2 months ago
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Any similar papers to this that they could start from?
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For now, the domain classifier is initialized in the DomainAwareModule. This leads to an unclear setup for new users because someone who wants to avoid adversarial can have to deal with domain classif…
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First off, I just want to say thank you for your amazing work on this repository! I've been learning a lot from it.
I’ve noticed that no matter which method of adversarial training I use, the clean…
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Hi! Thanks for sharing your work.
I would like to know are adversarial attacks also included in the benchmark? If yes, which type of attacks have been included?
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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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Does this project include the relevant codes for papers ‘Diffusion-Reinforcement Learning Hierarchical Motion Planning in Adversarial Multi-agent Games’ and ‘Diffusion Models for Multi-target Adversar…
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**Submitting author:** @melihcatal (Melih Catal)
**Repository:** https://github.com/melihcatal/advsecurenet
**Branch with paper.md** (empty if default branch): joss_paper
**Version:** V0.2.3
**Editor:…