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[Adversarial label-flipping attack and defense for graph neural networks](https://ieeexplore.ieee.org/abstract/document/9338299/)
[Adversarial_Label-Flipping_Attack_and_Defense_for_Graph_Neural_Netwo…
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Hello there,
Total dilettante here - I was wondering if its possible to create GANs with either the current version or V2 of Synaptic. If not then I'd be interested in any generative models (seems Sy…
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In case you guys haven't seen it, this paper came out recently and looks kind of interesting: https://arxiv.org/abs/1701.01329
My first couple read throughs leave me with some questions. The paper …
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https://arxiv.org/pdf/1801.02610.pdf
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### 論文へのリンク
[[arXiv:2006.12681] Contrastive Generative Adversarial Networks](https://arxiv.org/abs/2006.12681)
### 著者・所属機関
Minguk Kang, Jaesik Park
- Graduate School of Artificial Intellig…
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### 論文へのリンク
[[arXiv:2004.05472] Autoencoding Generative Adversarial Networks](https://arxiv.org/abs/2004.05472)
### 著者・所属機関
Conor Lazarou
- Flatland Data Solutions, Saskatoon, Canada
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## 一言でいうと
GANのmode collapse(似たような画像しか生成されなくなる問題)を防ぐため、lossにエントロピーの項を追加した研究。エントロピーが大きいほど分散が大きい=似た画像のみ乗せ生成を抑止できる。(周辺)エントロピーの計算は困難だが、直接不偏モンテカルロ推定で近似を行っている。
### 論文リンク
https://arxiv.org/abs/1910.0…
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Second paragraph ~
>But there is more to machine learning than just solving discriminative tasks. For example, given a large dataset, without any labels, we might want to **learn a model** that co…
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# Generative Adversarial Networks (GANs) | Analixa
Generative Adversarial Networks are used to generate images that never existed before. They learn about the world (objects, animals and so forth) an…