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Diffusion models exhibit excellent sample quality, but existing guidance methods often require additional model training or are limited to specific tasks.
Reverse-time diffusion equation models
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Estimation of non-normalized statistical models by score matching
Hyvärinen, A. and Dayan, P · 2005
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Path integrals and symmetry breaking for optimal control theory
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Kappen, H · 2008
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Efron, B · 2011
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A connection between score matching and denoising autoencoders
Vincent, P · 2011
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Optimal control as a graphical model inference problem
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Saleh, B. and Elgammal, A · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
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Adam: A method for stochastic optimization, 2017
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Demystifying MMD GANs
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Reinforcement learning and control as probabilistic inference: Tutorial and review, 2018
Levine, S · 2018
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A style-based generator architecture for generative adversarial networks
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Generative modeling by estimating gradients of the data distribution
Song, Y. and Ermon, S · 2019
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Denoising diffusion probabilistic models
Ho, J., Jain, A., and Abbeel, P · 2020
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Score-based generative modeling through stochastic differential equations
Song, Y., Sohl-Dickstein, J., Kingma, D. P., Kumar, A., Ermon, S., and Poole, B · 2020
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Diffusion models beat gans on image synthesis
Dhariwal, P. and Nichol, A · 2021
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Classifier-free diffusion guidance
Ho, J. and Salimans, T · 2021
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Detecting and adapting to irregular distribution shifts in bayesian online learning
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Denoising diffusion gamma models, 2021
Nachmani, E., Roman, R. S., and Wolf, L · 2021
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Learning transferable visual models from natural language supervision
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Explore image deblurring via encoded blur kernel space
Tran, P., Tran, A. T., Phung, Q., and Hoai, M · 2021
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Elucidating the design space of diffusion-based generative models
Beta diffusion
Zhou, M., Chen, T., Wang, Z., and Zheng, H · 2023
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Universal guidance for diffusion models
Bansal, A., Chu, H.-M., Schwarzschild, A., Sengupta, R., Goldblum, M., Geiping, J., and Goldstein, T · 2024
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An optimal control perspective on diffusion-based generative modeling
Berner, J., Richter, L., and Ullrich, K · 2024
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Tweedie moment projected diffusions for inverse problems
Boys, B., Girolami, M., Pidstrigach, J., Reich, S., Mosca, A., and Akyildiz, O. D · 2024
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Generative modeling with phase stochastic bridge
Chen, T., Gu, J., Dinh, L., Theodorou, E., Susskind, J. M., and Zhai, S · 2024
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A survey on diffusion models for inverse problems, 2024
Daras, G., Chung, H., Lai, C.-H., Mitsufuji, Y., Ye, J. C., Milanfar, P., Dimakis, A. G., and Delbracio, M · 2024
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Karras, T., Aittala, M., Aila, T., and Laine, S · 2022
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Denoising diffusion restoration models
Kawar, B., Elad, M., Ermon, S., and Song, J · 2022
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Repaint: Inpainting using denoising diffusion probabilistic models
Lugmayr, A., Danelljan, M., Romero, A., Yu, F., Timofte, R., and Van Gool, L · 2022
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High-resolution image synthesis with latent diffusion models
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Palette: Image-to-image diffusion models
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Scaling autoregressive models for content-rich text-to-image generation
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Building normalizing flows with stochastic interpolants
Albergo, M. and Vanden-Eijnden, E · 2023
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Symbolic music generation with non-differentiable rule guided diffusion
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Divide-and-conquer posterior sampling for denoising diffusion priors
Janati, Y., MOUFAD, B., Durmus, A. O., Moulines, E., and Olsson, J · 2024
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A variational perspective on solving inverse problems with diffusion models
Mardani, M., Song, J., Kautz, J., and Vahdat, A · 2024
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SDXL: Improving latent diffusion models for high-resolution image synthesis
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Training-free linear image inverses via flows
Pokle, A., Muckley, M. J., Chen, R. T. Q., and Karrer, B · 2024
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DMPlug: A plug-in method for solving inverse problems with diffusion models
Wang, H., Zhang, X., Li, T., Wan, Y., Chen, T., and Sun, J · 2024
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TFG: Unified training-free guidance for diffusion models
Ye, H., Lin, H., Han, J., Xu, M., Liu, S., Liang, Y., Ma, J., Zou, J., and Ermon, S · 2024
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Generator matching: Generative modeling with arbitrary markov processes
Holderrieth, P., Havasi, M., Yim, J., Shaul, N., Gat, I., Jaakkola, T., Karrer, B., Chen, R. T. Q., and Lipman, Y · 2025
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Heavy-tailed diffusion models
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