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https://github.com/ashwinpn/generative-models
Research and implementations/applications of Generative Models (GANs, VAEs, and Autoregressive models) and their applications
https://github.com/ashwinpn/generative-models
Last synced: about 5 hours ago
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Research and implementations/applications of Generative Models (GANs, VAEs, and Autoregressive models) and their applications
- Host: GitHub
- URL: https://github.com/ashwinpn/generative-models
- Owner: ashwinpn
- License: mit
- Created: 2020-03-09T01:03:06.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2020-05-23T09:44:20.000Z (over 4 years ago)
- Last Synced: 2023-10-19T22:45:53.216Z (about 1 year ago)
- Size: 1.17 MB
- Stars: 1
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
#### [Three Approaches to Generative Models](https://blog.openai.com/generative-models/)
- [Generative Adversarial Networks (GANs)]
- [Different Versions of GANs](#different-versions-of-gans)
- [GANs Comparision](#gans-comparision)
- [GANs Survey for Vision](#gans-survey-for-vision)
- [Variants of GAN Architecture](#variants-of-gan-architecture)
- [GAN Value Functions](#gan-value-functions)
- [References](#references)
- [Paper Review](#paper-review)
- [Variational Autoencoders (VAEs)]
- [Autoencoders](https://github.com/gopala-kr/autoencoders)
- [Autoregressive models]
- [EX: PixelRNN]
[Back to top](#three-approaches-to-generative-models)
-----------
#### Different Versions of GANs
[Back to top](#three-approaches-to-generative-models)
*(I have listed below GANs based on their [timelines](https://github.com/dongb5/GAN-Timeline), since from GANs inception(Jun 2014))*
- [DCGANs]
- [cGANs]
- [InfoGANs]
- [Wasserstein GANs]
- [LAPGAN]
- [GRAN ]
- [BiGANs]
- [f-GAN]
- [CoGAN]
- [EBGAN]
- [iGAN]
- [SeqGAN]
- [RenderGAN]
- [VGAN]
- [LSGANs]
- [IcGAN]
- [TGAN]
- [SAD-GAN]
- [C-RNN-GAN]
- [AANs]
- [StackGAN]
- [SGAN]
- [SalGAN]
- [AdaGAN]
- [GLS-GAN]
- [ArtGAN]
- [BS-GAN]
- [AM-GAN]
- [Triple-GAN]
- [DiscoGAN]
- [SEGAN]
- [CVAE-GAN]
- [SeGAN]
- [CycleGAN]
- [BEGAN]
- [MidiNet]
- [Semi-Latent GAN]
- [DualGAN]
- [A-Fast-RCNN]
- [MAGAN]
- [Gang of GANs]
- [Softmax GAN]
- [Show, Adapt and Tell]
- [Geometric GAN]
- [GeneGAN]
- [Flow-GAN]
- [SegAN]
- [DeLiGAN]
- [StackGAN]
- [Flow-GAN]
- [GraphGAN]
- [MuseGAN]
- [OptionGAN]
- [RAN4IQA]
- [Show, Reward and Tell]
More GANs --> [The GAN Zoo](https://github.com/hindupuravinash/the-gan-zoo)
----------------------------------------------------
#### References
[Back to top](#three-approaches-to-generative-models)
- Generative Adversarial Networks: An Overview [[arXiv]](https://arxiv.org/abs/1710.07035)
- [NIPS 2016 Tutorial:
Generative Adversarial Networks](https://arxiv.org/pdf/1701.00160.pdf)
- [Survey on Generative Adversarial Networks](https://pdfs.semanticscholar.org/0e1b/15ee5b4eec9b19eae9ae973a2ddc64f6cc72.pdf)
- [Comparative Study on Generative Adversarial Networks](https://arxiv.org/pdf/1801.04271.pdf)
- [GAN Lab: Understanding Complex Deep Generative Models using
Interactive Visual Experimentation](https://arxiv.org/pdf/1809.01587v1.pdf)
- [A Survey of Image Synthesis and Editing with Generative Adversarial
Networks](https://cg.cs.tsinghua.edu.cn/people/~kun/papers/gan_survey_final.pdf)
- [OpenAI: Generative Models](https://blog.openai.com/generative-models/)
- [Generative models](https://storage.googleapis.com/ml4a.github.io/Slides_06/assets/player/KeynoteDHTMLPlayer.html#0)
- [Adversarial Examples: Attacks and Defenses for Deep Learning](https://arxiv.org/pdf/1712.07107.pdf)
- [Generative Adversarial Nets for Information Retrieval: Fundamentals and Advances](https://arxiv.org/abs/1806.03577v1)
- [The GAN Landscape: Losses, Architectures, Regularization, and Normalization](https://arxiv.org/abs/1807.04720v1)
- [A Tale of Three Probabilistic Families: Discriminative, Descriptive
and Generative Models](https://arxiv.org/pdf/1810.04261v1.pdf)
- [QGAN: Quantized Generative Adversarial Networks](https://arxiv.org/abs/1901.08263v1)
-----------
#### Paper Review
[Back to top](#three-approaches-to-generative-models)
- [GAN-theory-and-ml](https://github.com/gopala-kr/GANs/blob/master/GAN-theory-and-ml.md)
- [GAN-ref-implementations](https://github.com/gopala-kr/GANs/blob/master/GAN-ref-implementations.md)
- [GAN-applications](https://github.com/gopala-kr/GANs/blob/master/GAN-applications.md)
- [GANs for vision](https://github.com/gopala-kr/GANs/blob/master/GAN-vision.md)
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