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About Self-Supervised Learning: Generative or Contrastive
This article surveys recent developments in self-supervised learning methods. It categorizes self-supervised learning approaches into three main categories: generative methods, contrastive methods, and generative-contrastive (adversarial) methods. The article reviews representative methods within each category, including generative models, contrastive coding, and deep infomax. It also discusses the theoretical foundations for why self-supervised learning works and outlines open problems and future directions.
Detailed Information
| Author: | ['IndritNallbani'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 20 |
| Language: | English |
| Format: | |
| Price: | FREE |
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