Generative Models

TitleMaterialsReferences
Generative ModelsSlides
Variational Auto EncodersSlides[1]
Generative Adversarial NetworksSlides[2] [3] [4]
Flow-Based ModelsSlides[5] [6] [7]
Auto-Regressive GenerationSlides[8] [9] [10] [11]
Vector QuantizationSlides[12] [13] [14]
Dall-ESlides[12] [15] [16] [17] [18] [19] [20]
Diffusion ModelsSlides[21] [22] [23]
Latent Diffusion and State-of-the-Art ModelsSlides[24] [15] [25] [26] [27] [28] [29] [30]
Which Generative Model Should I Use?Slides

References

  1. Auto-Encoding Variational BayesDiederik P Kingma, Max Welling2013
  2. Generative Adversarial NetworksIan J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, etal.2014
  3. Large Scale GAN Training for High Fidelity Natural Image SynthesisAndrew Brock, Jeff Donahue, Karen Simonyan2018
  4. Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial NetworkChristian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, Alejandro Acosta, etal.2016
  5. Variational Inference with Normalizing FlowsDanilo Jimenez Rezende, Shakir Mohamed2015
  6. Density estimation using Real NVPLaurent Dinh, Jascha Sohl-Dickstein, Samy Bengio2016
  7. Glow: Generative Flow with Invertible 1x1 ConvolutionsDiederik P. Kingma, Prafulla Dhariwal2018
  8. WaveNet: A Generative Model for Raw AudioAaron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, etal.2016
  9. Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive TransformerSongwei Ge, Thomas Hayes, Harry Yang, Xi Yin, Guan Pang, David Jacobs, Jia-Bin Huang, Devi Parikh2022
  10. Lossless Image Compression through Super-ResolutionSheng Cao, Chao-Yuan Wu, Philipp Krähenbühl2020
  11. Practical Full Resolution Learned Lossless Image CompressionFabian Mentzer, Eirikur Agustsson, Michael Tschannen, Radu Timofte, Luc Van Gool2018
  12. Neural Discrete Representation LearningAaron van den Oord, Oriol Vinyals, Koray Kavukcuoglu2017
  13. Taming Transformers for High-Resolution Image SynthesisPatrick Esser, Robin Rombach, Björn Ommer2020
  14. Language Model Beats Diffusion -- Tokenizer is Key to Visual GenerationLijun Yu, José Lezama, Nitesh B. Gundavarapu, Luca Versari, Kihyuk Sohn, David Minnen, etal.2023
  15. Zero-Shot Text-to-Image GenerationAditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, etal.2021
  16. Language Models are Unsupervised Multitask LearnersAlec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever2019
  17. Simulating 500 million years of evolution with a language modelThomas Hayes, Roshan Rao, Halil Akin, Nicholas J. Sofroniew, Deniz Oktay, etal.2024
  18. Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image CaptioningPiyush Sharma, Nan Ding, Sebastian Goodman, Radu Soricut2018
  19. YFCC100M: The New Data in Multimedia ResearchBart Thomee, David A. Shamma, Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, etal.2015
  20. Generating Long Sequences with Sparse TransformersRewon Child, Scott Gray, Alec Radford, Ilya Sutskever2019
  21. Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter Abbeel2020
  22. Generative Modeling by Estimating Gradients of the Data DistributionYang Song, Stefano Ermon2019
  23. Diffusion Models Beat GANs on Image SynthesisPrafulla Dhariwal, Alex Nichol2021
  24. High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, Björn Ommer2021
  25. Photorealistic Text-to-Image Diffusion Models with Deep Language UnderstandingChitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, etal.2022
  26. Hierarchical Text-Conditional Image Generation with CLIP LatentsAditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, Mark Chen2022
  27. CCM: Adding Conditional Controls to Text-to-Image Consistency ModelsJie Xiao, Kai Zhu, Han Zhang, Zhiheng Liu, Yujun Shen, Yu Liu, Xueyang Fu, Zheng-Jun Zha2023
  28. Adding Conditional Control to Text-to-Image Diffusion ModelsLvmin Zhang, Anyi Rao, Maneesh Agrawala2023
  29. One-step Diffusion with Distribution Matching DistillationTianwei Yin, Michaël Gharbi, Richard Zhang, Eli Shechtman, Fredo Durand, William T. Freeman, etal.2023
  30. Diffusion Models: A Comprehensive Survey of Methods and ApplicationsLing Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Wentao Zhang, Bin Cui, etal.2022