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We propose a simple, training-free mechanism which explains the generalization behaviour of diffusion models.
Dynamic programming
Bellman, R · 1966
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Multiresolution sampling procedure for analysis and synthesis of texture images
De Bonet, J. S · 1997
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Texture synthesis by non-parametric sampling
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Fields of experts: A framework for learning image priors
Roth, S. and Black, M. J · 2005
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Image denoising via sparse and redundant representations over learned dictionaries
Elad, M. and Aharon, M · 2006
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Summarizing visual data using bidirectional similarity
Simakov, D., Caspi, Y., Shechtman, E., and Irani, M · 2008
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Patchmatch: A randomized correspondence algorithm for structural image editing
Barnes, C., Shechtman, E., Finkelstein, A., and Goldman, D. B · 2009
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Learning multiple layers of features from tiny images
Krizhevsky, A., Hinton, G., et al · 2009
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A connection between score matching and denoising autoencoders
Vincent, P · 2011
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From learning models of natural image patches to whole image restoration
Zoran, D. and Weiss, Y · 2011
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Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Sohl-Dickstein, J., Weiss, E., Maheswaranathan, N., and Ganguli, S · 2015
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., and Hochreiter, S · 2017
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A style-based generator architecture for generative adversarial networks
Karras, T., Laine, S., and Aila, T · 2019
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On the spectral bias of neural networks
Rahaman, N., Baratin, A., Arpit, D., Draxler, F., Lin, M., Hamprecht, F., Bengio, Y., and Courville, A · 2019
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Singan: Learning a generative model from a single natural image
Shaham, T. R., Dekel, T., and Michaeli, T · 2019
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Stargan v2: Diverse image synthesis for multiple domains
Choi, Y., Uh, Y., Yoo, J., and Ha, J.-W · 2020
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Denoising diffusion probabilistic models
Ho, J., Jain, A., and Abbeel, P · 2020
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Posterior sampling for image restoration using explicit patch priors
Friedman, R. and Weiss, Y · 2021
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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 · 2021
Sinfusion: Training diffusion models on a single image or video
Nikankin, Y., Haim, N., and Irani, M · 2023
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Scalable diffusion models with transformers
Peebles, W. and Xie, S · 2023
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Scarvelis, C., Borde, H. S. d. O., and Solomon, J · 2023
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Diffusion art or digital forgery? investigating data replication in diffusion models
Somepalli, G., Singla, V., Goldblum, M., Geiping, J., and Goldstein, T · 2023
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Patch diffusion: Faster and more data-efficient training of diffusion models
Wang, Z., Jiang, Y., Zheng, H., Wang, P., He, P., Wang, Z., Chen, W., and Zhou, M · 2023
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Stable target field for reduced variance score estimation in diffusion models
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All are worth words: a vit backbone for score-based diffusion models
Bao, F., Li, C., Cao, Y., and Zhu, J · 2022
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Inductive biases for deep learning of higher-level cognition
Goyal, A. and Bengio, Y · 2022
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Flexible diffusion modeling of long videos
Harvey, W., Naderiparizi, S., Masrani, V., Weilbach, C., and Wood, F · 2022
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Elucidating the design space of diffusion-based generative models
Karras, T., Aittala, M., Aila, T., and Laine, S · 2022
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A self-supervised descriptor for image copy detection
Pizzi, E., Roy, S. D., Ravindra, S. N., Goyal, P., and Douze, M · 2022
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High-resolution image synthesis with latent diffusion models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., and Ommer, B · 2022
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Xu, Y., Tong, S., and Jaakkola, T. S · 2023
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On the generalization of diffusion model
Yi, M., Sun, J., and Li, Z · 2023
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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 · 2023
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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
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An analytic theory of creativity in convolutional diffusion models
Kamb, M. and Ganguli, S · 2024
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Understanding generalizability of diffusion models requires rethinking the hidden gaussian structure
Li, X., Dai, Y., and Qu, Q · 2024
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Nearest neighbour score estimators for diffusion generative models
Niedoba, M., Green, D., Naderiparizi, S., Lioutas, V., Lavington, J. W., Liang, X., Liu, Y., Zhang, K., Dabiri, S., Ścibior, A., Zwartsenberg, B., and Wood, F · 2024
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Wang, B. and Vastola, J. J · 2024
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Sindiffusion: Learning a diffusion model from a single natural image
Wang, W., Bao, J., Zhou, W., Chen, D., Chen, D., Yuan, L., and Li, H · 2025
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