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Sampling algorithms play an important role in controlling the quality and runtime of diffusion model inference.
Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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The randomized midpoint method for log-concave sampling
Ruoqi Shen and Yin Tat Lee · 2019
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On the ergodicity, bias and asymptotic normality of randomized midpoint sampling method
Ye He, Krishnakumar Balasubramanian, and Murat A Erdogdu · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Diffwave: A versatile diffusion model for audio synthesis
Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, and Bryan Catanzaro · 2020
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Diffusion Schrödinger bridge with applications to score-based generative modeling
Valentin De Bortoli, James Thornton, Jeremy Heng, and Arnaud Doucet · 2021
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Diffusion models beat GANs on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Is there an analog of nesterov acceleration for gradient-based mcmc?
Yi-An Ma, Niladri S Chatterji, Xiang Cheng, Nicolas Flammarion, Peter L Bartlett, and Michael I Jordan · 2021
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Maximum likelihood training of score-based diffusion models
Yang Song, Conor Durkan, Iain Murray, and Stefano Ermon · 2021
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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 · 2021
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Score-based generative modeling in latent space
Arash Vahdat, Karsten Kreis, and Jan Kautz · 2021
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Generative modeling with denoising auto-encoders and Langevin sampling
Adam Block, Youssef Mroueh, and Alexander Rakhlin · 2022
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Convergence of denoising diffusion models under the manifold hypothesis
Valentin De Bortoli · 2022
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Convergence for score-based generative modeling with polynomial complexity
Holden Lee, Jianfeng Lu, and Yixin Tan · 2022
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Let us build bridges: Understanding and extending diffusion generative models
Xingchao Liu, Lemeng Wu, Mao Ye, and Qiang Liu · 2022
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Score-based generative models detect manifolds
Jakiw Pidstrigach · 2022
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Convergence in KL divergence of the inexact Langevin algorithm with application to score-based generative models
Andre Wibisono and Kaylee Y. Yang · 2022
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Faster high-accuracy log-concave sampling via algorithmic warm starts
Jason M Altschuler and Sinho Chewi · 2023
Cited alongside, same era.
Parallel discrete sampling via continuous walks
Nima Anari, Yizhi Huang, Tianyu Liu, Thuy-Duong Vuong, Brian Xu, and Katherine Yu · 2023
Cited alongside, same era.
Towards faster non-asymptotic convergence for diffusion-based generative models
Gen Li, Yuting Wei, Yuxin Chen, and Yuejie Chi · 2023
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Langevin monte carlo for strongly log-concave distributions: Randomized midpoint revisited
Lu Yu, Avetik Karagulyan, and Arnak Dalalyan · 2023
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Improved discretization analysis for underdamped langevin monte carlo
Shunshi Zhang, Sinho Chewi, Mufan Li, Krishna Balasubramanian, and Murat A Erdogdu · 2023
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Fast parallel sampling under isoperimetry
Nima Anari, Sinho Chewi, and Thuy-Duong Vuong · 2024
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Nearly d-linear convergence bounds for diffusion models via stochastic localization
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Joe Benton, George Deligiannidis, and Arnaud Doucet · 2023
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Improving image generation with better captions
James Betker, Gabriel Goh, Li Jing, Tim Brooks, Jianfeng Wang, Linjie Li, Long Ouyang, Juntang Zhuang, Joyce Lee, Yufei Guo, et al · 2023
Cited alongside, same era.
The probability flow ODE is provably fast
Sitan Chen, Sinho Chewi, Holden Lee, Yuanzhi Li, Jianfeng Lu, and Adil Salim · 2023
Cited alongside, same era.
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions
Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, and Anru R Zhang · 2023
Cited alongside, same era.
Restoration-degradation beyond linear diffusions: A non-asymptotic analysis for ddim-type samplers
Sitan Chen, Giannis Daras, and Alex Dimakis · 2023
Cited alongside, same era.
Log-concave sampling
Sinho Chewi · 2023
Cited alongside, same era.
Improved analysis of score-based generative modeling: User-friendly bounds under minimal smoothness assumptions
Hongrui Chen, Holden Lee, and Jianfeng Lu · 2023
Cited alongside, same era.
Joe Benton, Valentin De Bortoli, Arnaud Doucet, and George Deligiannidis · 2024
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Video generation models as world simulators
Tim Brooks, Bill Peebles, Connor Holmes, Will DePue, Yufei Guo, Li Jing, David Schnurr, Joe Taylor, Troy Luhman, Eric Luhman, Clarence Ng, Ricky Wang, and Aditya Ramesh · 2024
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Accelerating diffusion models with parallel sampling: Inference at sub-linear time complexity, 2024
Haoxuan Chen, Yinuo Ren, Lexing Ying, and Grant M. Rotskoff · 2024
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Theory of consistency diffusion models: Distribution estimation meets fast sampling
Zehao Dou, Minshuo Chen, Mengdi Wang, and Zhuoran Yang · 2024
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Scaling rectified flow transformers for high-resolution image synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, et al · 2024
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The poisson midpoint method for langevin dynamics: Provably efficient discretization for diffusion models, 2024
Saravanan Kandasamy and Dheeraj Nagaraj · 2024
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Accelerating convergence of score-based diffusion models, provably
Gen Li, Yu Huang, Timofey Efimov, Yuting Wei, Yuejie Chi, and Yuxin Chen · 2024
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Parallel sampling of diffusion models
Andy Shih, Suneel Belkhale, Stefano Ermon, Dorsa Sadigh, and Nima Anari · 2024
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Protein structure generation via folding diffusion
Kevin E Wu, Kevin K Yang, Rianne van den Berg, Sarah Alamdari, James Y Zou, Alex X Lu, and Ava P Amini · 2024
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Parallelized midpoint randomization for langevin monte carlo
Lu Yu and Arnak Dalalyana · 2024
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