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Diffusion models have achieved huge empirical success in data generation tasks.
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Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, and Max Welling, Argmax flows and multinomial diffusion: Learning categorical distributions , 2021
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Alex Nichol and Prafulla Dhariwal, Improved denoising diffusion probabilistic models , 2021
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Zhiye Guo, Jian Liu, Yanli Wang, Mengrui Chen, Duolin Wang, Dong Xu, and Jianlin Cheng, Diffusion models in bioinformatics: A new wave of deep learning revolution in action , 2023
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2022
Cited alongside, same era.
Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, and Anru R. Zhang, Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions , 2022
2022
Cited alongside, same era.
2022
Cited alongside, same era.
Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J. Fleet, Video diffusion models , 2022
2022
Cited alongside, same era.
Holden Lee, Jianfeng Lu, and Yixin Tan, Convergence for score-based generative modeling with polynomial complexity , 2022
2022
Cited alongside, same era.
Ruihan Yang, Prakhar Srivastava, and Stephan Mandt, Diffusion probabilistic modeling for video generation , 2022
2022
Cited alongside, same era.
Jacob Austin, Daniel D. Johnson, Jonathan Ho, Daniel Tarlow, and Rianne van den Berg, Structured denoising diffusion models in discrete state-spaces , 2023
2023
Cited alongside, same era.
Joe Benton, Valentin De Bortoli, Arnaud Doucet, and George Deligiannidis, Linear convergence bounds for diffusion models via stochastic localization , 2023
2023
Cited alongside, same era.
Han Huang, Leilei Sun, Bowen Du, and Weifeng Lv, Conditional diffusion based on discrete graph structures for molecular graph generation , 2023
2023
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Aaron Lou, Chenlin Meng, and Stefano Ermon, Discrete diffusion language modeling by estimating the ratios of the data distribution , 2023
2023
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Gen Li, Yuting Wei, Yuxin Chen, and Yuejie Chi, Towards faster non-asymptotic convergence for diffusion-based generative models , 2023
2023
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Chenlin Meng, Kristy Choi, Jiaming Song, and Stefano Ermon, Concrete score matching: Generalized score matching for discrete data , 2023
2023
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Flavio Schneider, Archisound: Audio generation with diffusion , 2023
2023
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Javier E Santos, Zachary R. Fox, Nicholas Lubbers, and Yen Ting Lin, Blackout diffusion: Generative diffusion models in discrete-state spaces , 2023
2023
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Haoran Sun, Lijun Yu, Bo Dai, Dale Schuurmans, and Hanjun Dai, Score-based continuous-time discrete diffusion models , 2023
2023
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Lin Zheng, Jianbo Yuan, Lei Yu, and Lingpeng Kong, A reparameterized discrete diffusion model for text generation , 2023
2023
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Puheng Li, Zhong Li, Huishuai Zhang, and Jiang Bian, On the generalization properties of diffusion models , 2024
2024
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