Update README.md

6-Disentangled Representation/README.md

@@ -6,15 +6,44 @@ A collection of resources on generative models which utilize generator functions
 
 
 
+## Introduction
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+The **disentangled representation learning** is first introduced in [Bengio et al. Representation learning: A review and new perspectives. PAMI, 2013]. This is to say that each scalar of the representation only encodes a single independent factor.
+
 
 
 ## Literature
 
+- [beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework](https://openreview.net/forum?id=Sy2fzU9gl)
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 - [Variational Inference of Disentangled Latent Concepts from Unlabeled Observations](https://arxiv.org/abs/1711.00848)  
   **[`ICLR 2018`]** *Abhishek Kumar, Prasanna Sattigeri, Avinash Balakrishnan* 
 
 - [Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations](https://arxiv.org/abs/1811.12359)  
   **[`arXiv 2018`]** *Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem* 
 
+- [Rethinking Content and Style Exploring Bias for Unsupervised
+  Disentanglement](http://arxiv.org/abs/2102.10544)  
+  **[`arXiv 2021`]** *Xuanchi Ren, Tao Yang, Yuwang Wang, Wenjun Zeng*
+
 - [Learning Disentangled Representation by Exploiting Pretrained Generative Models: A Contrastive Learning View](https://arxiv.org/abs/2102.10543)  
   **[`ICLR 2022`]** *Xuanchi Ren, Tao Yang, Yuwang Wang, Wenjun Zeng* 
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+- [Disentangled Representation Learning](http://arxiv.org/abs/2211.11695)  
+  **[`arXiv 2022`]** *Xin Wang, Hong Chen, Si'ao Tang, Zihao Wu, Wenwu Zhu*
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+
+
+## Related 
+
+Compositional Generalization: people exhibit the capacity to understand and produce a potentially infinite number of novel combinations of known components. As Chomsky said, to make “infinite use of finite means.”
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+https://blog.research.google/2020/03/measuring-compositional-generalization.html
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+独立的研究可能不是足够充分的，应该是在你的模型框架下去探究解耦的可能性，这应该是模型本身所应该具备的能力。
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