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Diffusion models, which convert noise into new data instances by learning to reverse a diffusion process, have become a cornerstone in contemporary generative modeling.
Reverse-time diffusion equation models
Anderson, B. D. (1982) · 1982
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Time reversal of diffusions
Haussmann, U. G. and Pardoux, E. (1986) · 1986
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Generative modeling with denoising auto-encoders and Langevin sampling
Block, A., Mroueh, Y., and Rakhlin, A. (2020) · 2002
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Estimation of non-normalized statistical models by score matching
Hyvärinen, A. (2005) · 2005
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Some extensions of score matching
Hyvärinen, A. (2007) · 2007
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Message-passing algorithms for compressed sensing
Donoho, D. L., Maleki, A., and Montanari, A. (2009) · 2009
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Introduction to nonparametric estimation
Tsybakov, A. B. (2009) · 2009
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Denoising diffusion implicit models
Song, J., Meng, C., and Ermon, S. (2020a) · 2010
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A connection between score matching and denoising autoencoders
Vincent, P. (2011) · 2011
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Linear estimating equations for exponential families with application to Gaussian linear concentration models
Forbes, P. G. and Lauritzen, S. (2015) · 2015
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Random processes for engineers
Hajek, B. (2015) · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Sohl-Dickstein, J., Weiss, E., Maheswaranathan, N., and Ganguli, S. (2015) · 2015
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Generative modeling by estimating gradients of the data distribution
Song, Y. and Ermon, S. (2019) · 2019
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Taming correlations through entropy-efficient measure decompositions with applications to mean-field approximation
Eldan, R. (2020) · 2020
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Denoising diffusion probabilistic models
Ho, J., Jain, A., and Abbeel, P. (2020) · 2020
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Structured denoising diffusion models in discrete state-spaces
Austin, J., Johnson, D. D., Ho, J., Tarlow, D., and van den Berg, R. (2021) · 2021
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WaveGrad: Estimating gradients for waveform generation
Chen, N., Zhang, Y., Zen, H., Weiss, R. J., Norouzi, M., and Chan, W. (2021) · 2021
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Diffusion Schrödinger bridge with applications to score-based generative modeling
De Bortoli, V., Thornton, J., Heng, J., and Doucet, A. (2021) · 2021
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Diffusion models beat GANs on image synthesis
Dhariwal, P. and Nichol, A. (2021) · 2021
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Adversarial score matching and improved sampling for image generation
Jolicoeur-Martineau, A., Piché-Taillefer, R., Mitliagkas, I., and des Combes, R. T. (2021) · 2021
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DiffWave: A versatile diffusion model for audio synthesis
Kong, Z., Ping, W., Huang, J., Zhao, K., and Catanzaro, B. (2021) · 2021
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Convergence of denoising diffusion models under the manifold hypothesis
De Bortoli, V. (2022) · 2022
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An information-theoretic view of stochastic localization
El Alaoui, A. and Montanari, A. (2022) · 2022
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Sampling from the sherrington-kirkpatrick gibbs measure via algorithmic stochastic localization
El Alaoui, A., Montanari, A., and Sellke, M. (2022) · 2022
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Classifier-free diffusion guidance
Ho, J. and Salimans, T. (2022) · 2022
Cited alongside, same era.
Elucidating the design space of diffusion-based generative models
Karras, T., Aittala, M., Aila, T., and Laine, S. (2022) · 2022
Cited alongside, same era.
Score-based generative modeling secretly minimizes the wasserstein distance
Kwon, D., Fan, Y., and Lee, K. (2022) · 2022
Cited alongside, same era.
Convergence for score-based generative modeling with polynomial complexity
Lee, H., Lu, J., and Tan, Y. (2022) · 2022
Cited alongside, same era.
A non-asymptotic framework for approximate message passing in spiked models
Li, G. and Wei, Y. (2022) · 2022
Cited alongside, same era.
A theoretical justification for image inpainting using denoising diffusion probabilistic models
Rout, L., Parulekar, A., Caramanis, C., and Shakkottai, S. (2023) · 2023
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Consistency models
Song, Y., Dhariwal, P., Chen, M., and Sutskever, I. (2023) · 2023
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Nearly d-linear convergence bounds for diffusion models via stochastic localization
Benton, J., De Bortoli, V., Doucet, A., and Deligiannidis, G. (2024) · 2024
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Dynamical regimes of diffusion models
Biroli, G., Bonnaire, T., De Bortoli, V., and Mézard, M. (2024) · 2024
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Convergence analysis of discrete diffusion model: Exact implementation through uniformization
Chen, H. and Ying, L. (2024) · 2024
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Liu, X., Wu, L., Ye, M., and Liu, Q. (2022) · 2022
Cited alongside, same era.
Score-based generative models detect manifolds
Pidstrigach, J. (2022) · 2022
Cited alongside, same era.
Hierarchical text-conditional image generation with CLIP latents
Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., and Chen, M. (2022) · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., and Ommer, B. (2022) · 2022
Cited alongside, same era.
Photorealistic text-to-image diffusion models with deep language understanding
Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E. L., Ghasemipour, K., Gontijo Lopes, R., Karagol Ayan, B., Salimans, T., et al. (2022) · 2022
Cited alongside, same era.
Wibisono, A. and Yang, K. Y. (2022) · 2022
Cited alongside, same era.
Diffusion models: A comprehensive survey of methods and applications
Yang, L., Zhang, Z., Song, Y., Hong, S., Xu, R., Zhao, Y., Shao, Y., Zhang, W., Cui, B., and Yang, M.-H. (2022) · 2022
Cited alongside, same era.
Convergence of flow-based generative models via proximal gradient descent in Wasserstein space
Cheng, X., Lu, J., Tan, Y., and Xie, Y. (2024) · 2024
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Provable statistical rates for consistency diffusion models
Dou, Z., Chen, M., Wang, M., and Yang, Z. (2024) · 2024
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Optimal convex m m -estimation via score matching
Feng, O. Y., Kao, Y.-C., Xu, M., and Samworth, R. J. (2024) · 2024
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Unveil conditional diffusion models with classifier-free guidance: A sharp statistical theory
Fu, H., Yang, Z., Wang, M., and Chen, M. (2024) · 2024
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Convergence analysis for general probability flow odes of diffusion models in wasserstein distances
Gao, X. and Zhu, L. (2024) · 2024
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Convergence of continuous normalizing flows for learning probability distributions
Gao, Y., Huang, J., Jiao, Y., and Zheng, S. (2024) · 2024
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Faster diffusion-based sampling with randomized midpoints: Sequential and parallel
Gupta, S., Cai, L., and Chen, S. (2024) · 2024
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Convergence analysis of probability flow ODE for score-based generative models
Huang, D. Z., Huang, J., and Lin, Z. (2024) · 2024
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Generalization in diffusion models arises from geometry-adaptive harmonic representations
Kadkhodaie, Z., Guth, F., Simoncelli, E. P., and Mallat, S. (2024) · 2024
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Adapting to unknown low-dimensional structures in score-based diffusion models
Li, G. and Yan, Y. (2024) · 2024
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Critical windows: non-asymptotic theory for feature emergence in diffusion models
Li, M. and Chen, S. (2024) · 2024
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Non-asymptotic convergence of discrete-time diffusion models: New approach and improved rate
Liang, Y., Ju, P., Liang, Y., and Shroff, N. (2024) · 2024
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Provably efficient posterior sampling for sparse linear regression via measure decomposition
Montanari, A. and Wu, Y. (2024) · 2024
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Diffusion model learns low-dimensional distributions via subspace clustering
Wang, P., Zhang, H., Zhang, Z., Chen, S., Ma, Y., and Qu, Q. (2024) · 2024
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Theoretical insights for diffusion guidance: A case study for gaussian mixture models
Wu, Y., Chen, M., Li, Z., Wang, M., and Wei, Y. (2024) · 2024
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Normalizing flow neural networks by JKO scheme
Xu, C., Cheng, X., and Xie, Y. (2024) · 2024
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Provably robust score-based diffusion posterior sampling for plug-and-play image reconstruction
Xu, X. and Chi, Y. (2024) · 2024
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The emergence of reproducibility and consistency in diffusion models
Zhang, H., Zhou, J., Lu, Y., Guo, M., Wang, P., Shen, L., and Qu, Q. (2024) · 2024
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