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Diffusion models may be formulated as a time-indexed sequence of energy-based models, where the score corresponds to the negative gradient of an energy function.
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Diffusion models beat gans on image synthesis
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Y. Du, S. Li, Y. Sharma, J. Tenenbaum, and I. Mordatch · 2021
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Learning transferable visual models from natural language supervision
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Should EBMs model the energy or the score?
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Y. Song, J. Sohl-Dickstein, D. P. Kingma, A. Kumar, S. Ermon, and B. Poole · 2021
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Score-based generative modeling in latent space
A. Vahdat, K. Kreis, and J. Kautz · 2021
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Diffusion normalizing flow
Q. Zhang and Y. Chen · 2021
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Learning energy-based models by cooperative diffusion recovery likelihood
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Classifier-free guidance is a predictor-corrector
A. Bradley and P. Nakkiran · 2024
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G. Cardoso, Y. J. el idrissi, S. L. Corff, and E. Moulines · 2024
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On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models
C. Horvat and J.-P. Pfister · 2024
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Variance reduction of diffusion model’s gradients with taylor approximation-based control variate
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Simple reflow: Improved techniques for fast flow models
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Dynamic negative guidance of diffusion models
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Improving the training of rectified flows
S. Lee, Z. Lin, and G. Fanti · 2024
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Derivative-free guidance in continuous and discrete diffusion models with soft value-based decoding
X. Li, Y. Zhao, C. Wang, G. Scalia, G. Eraslan, S. Nair, T. Biancalani, S. Ji, A. Regev, S. Levine, et al · 2024
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Correcting diffusion generation through resampling
Y. Liu, Y. Zhang, T. Jaakkola, and S. Chang · 2024
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Particle denoising diffusion sampler
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Energy discrepancies: a score-independent loss for energy-based models
T. Schröder, Z. Ou, J. Lim, Y. Li, S. Vollmer, and A. Duncan · 2024
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The superposition of diffusion models using the itô density estimator
M. Skreta, L. Atanackovic, A. J. Bose, A. Tong, and K. Neklyudov · 2024
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Practical and asymptotically exact conditional sampling in diffusion models
L. Wu, B. Trippe, C. Naesseth, D. Blei, and J. P. Cunningham · 2024
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Energy-based diffusion language models for text generation
M. Xu, T. Geffner, K. Kreis, W. Nie, Y. Xu, J. Leskovec, S. Ermon, and A. Vahdat · 2024
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Tfg: Unified training-free guidance for diffusion models
H. Ye, H. Lin, J. Han, M. Xu, S. Liu, Y. Liang, J. Ma, J. Zou, and S. Ermon · 2024
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Mechanisms of projective composition of diffusion models
A. Bradley, P. Nakkiran, D. Berthelot, J. Thornton, and J. M. Susskind · 2025
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Debiasing guidance for discrete diffusion with sequential monte carlo
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A general framework for inference-time scaling and steering of diffusion models
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