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Diffusion models have seen notable success in continuous domains, leading to the development of discrete diffusion models (DDMs) for discrete variables.
Stochastic simulation of chemical kinetics
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Markov chain approximation and measure change for time-inhomogeneous stochastic processes
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Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu · 2022
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Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, and Tommi Jaakkola · 2023
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Generative flows on discrete state-spaces: Enabling multimodal flows with applications to protein co-design
Andrew Campbell, Jason Yim, Regina Barzilay, Tom Rainforth, and Tommi Jaakkola · 2024
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Justin Deschenaux and Caglar Gulcehre · 2024
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Concrete score matching: Generalized score matching for discrete data
Chenlin Meng, Kristy Choi, Jiaming Song, and Stefano Ermon · 2022
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Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, and Anru R Zhang · 2023
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Jiaming Song, Chenlin Meng, and Stefano Ermon
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole
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Itai Gat, Tal Remez, Neta Shaul, Felix Kreuk, Ricky TQ Chen, Gabriel Synnaeve, Yossi Adi, and Yaron Lipman · 2024
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Discrete diffusion language modeling by estimating the ratios of the data distribution
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Simplified and generalized masked diffusion for discrete data
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