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Score-based generative models have emerged as a powerful approach for sampling high-dimensional probability distributions.
Towards the ultimate conservative difference scheme. ii. monotonicity and conservation combined in a second-order scheme
B. Van Leer · 1974
Earlier work this paper cites.
Transport equation and Cauchy problem for BV vector fields
L. Ambrosio · 2004
Earlier work this paper cites.
Estimation of non-normalized statistical models by score matching
A. Hyvärinen and P. Dayan · 2005
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A connection between score matching and denoising autoencoders
P. Vincent · 2011
Earlier work this paper cites.
Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2013
Earlier work this paper cites.
Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
Earlier work this paper cites.
Variational inference with normalizing flows
D. Rezende and S. Mohamed · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
J. Sohl-Dickstein, E. Weiss, N. Maheswaranathan, and S. Ganguli · 2015
Earlier work this paper cites.
Density estimation for statistics and data analysis
B. W. Silverman · 2018
Earlier work this paper cites.
On the spectral bias of neural networks
N. Rahaman, A. Baratin, D. Arpit, F. Draxler, M. Lin, F. Hamprecht, Y. Bengio, and A. Courville · 2019
Earlier work this paper cites.
Generative modeling by estimating gradients of the data distribution
Y. Song and S. Ermon · 2019
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Frequency principle: Fourier analysis sheds light on deep neural networks
Z.-Q. J. Xu, Y. Zhang, T. Luo, Y. Xiao, and Z. Ma · 2019
Earlier work this paper cites.
Generative modeling with denoising auto-encoders and langevin sampling
A. Block, Y. Mroueh, and A. Rakhlin · 2020
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Jukebox: A generative model for music
P. Dhariwal, H. Jun, C. Payne, J. W. Kim, A. Radford, and I. Sutskever · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
J. Ho, A. Jain, and P. Abbeel · 2020
Earlier work this paper cites.
Denoising diffusion implicit models
J. Song, C. Meng, and S. Ermon · 2020
Earlier work this paper cites.
Score-based generative modeling through stochastic differential equations
Y. Song, J. Sohl-Dickstein, D. P. Kingma, A. Kumar, S. Ermon, and B. Poole · 2020
Earlier work this paper cites.
Diffusion schrödinger bridge with applications to score-based generative modeling
V. De Bortoli, J. Thornton, J. Heng, and A. Doucet · 2021
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Diffusion models beat gans on image synthesis
P. Dhariwal and A. Nichol · 2021
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Detailed proof of classical Gagliardo-Nirenberg interpolation inequality with historical remarks
A. Fiorenza, M. R. Formica, T. G. Roskovec, and F. Soudský · 2021
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Normalizing flows for probabilistic modeling and inference
G. Papamakarios, E. Nalisnick, D. J. Rezende, S. Mohamed, and B. Lakshminarayanan · 2021
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Grad-tts: A diffusion probabilistic model for text-to-speech
V. Popov, I. Vovk, V. Gogoryan, T. Sadekova, and M. Kudinov · 2021
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Error bounds for flow matching methods
J. Benton, G. Deligiannidis, and A. Doucet · 2023
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Probability flow solution of the fokker–planck equation
N. M. Boffi and E. Vanden-Eijnden · 2023
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Improved analysis of score-based generative modeling: User-friendly bounds under minimal smoothness assumptions
H. Chen, H. Lee, and J. Lu · 2023
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Score approximation, estimation and distribution recovery of diffusion models on low-dimensional data
M. Chen, K. Huang, T. Zhao, and M. Wang · 2023
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Restoration-degradation beyond linear diffusions: A non-asymptotic analysis for ddim-type samplers
S. Chen, G. Daras, and A. Dimakis · 2023
Later among the works it cites.
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M. S. Albergo and E. Vanden-Eijnden · 2022
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Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions
S. Chen, S. Chewi, J. Li, Y. Li, A. Salim, and A. R. Zhang · 2022
Cited alongside, same era.
Score-based generative modeling secretly minimizes the wasserstein distance
D. Kwon, Y. Fan, and K. Lee · 2022
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Convergence for score-based generative modeling with polynomial complexity
H. Lee, J. Lu, and Y. Tan · 2022
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Flow matching for generative modeling
Y. Lipman, R. T. Chen, H. Ben-Hamu, M. Nickel, and M. Le · 2022
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Flow straight and fast: Learning to generate and transfer data with rectified flow
X. Liu, C. Gong, and Q. Liu · 2022
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Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps
C. Lu, Y. Zhou, F. Bao, J. Chen, C. Li, and J. Zhu · 2022
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Convergence of score-based generative modeling for general data distributions
H. Lee, J. Lu, and Y. Tan · 2023
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Towards faster non-asymptotic convergence for diffusion-based generative models
G. Li, Y. Wei, Y. Chen, and Y. Chi · 2023
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The probability flow ode is provably fast
S. Chen, S. Chewi, H. Lee, Y. Li, J. Lu, and A. Salim · 2024
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Scaling rectified flow transformers for high-resolution image synthesis
P. Esser, S. Kulal, A. Blattmann, R. Entezari, J. Müller, H. Saini, Y. Levi, D. Lorenz, A. Sauer, F. Boesel, et al · 2024
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Convergence analysis for general probability flow odes of diffusion models in wasserstein distances
X. Gao and L. Zhu · 2024
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Accelerating convergence of score-based diffusion models, provably
G. Li, Y. Huang, T. Efimov, Y. Wei, Y. Chi, and Y. Chen · 2024
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C. Mooney, Z. Wang, J. Xin, and Y. Yu · 2024
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Contractive diffusion probabilistic models
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Score-based diffusion models via stochastic differential equations–a technical tutorial
W. Tang and H. Zhao · 2024
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Theoretical insights for diffusion guidance: A case study for gaussian mixture models
Y. Wu, M. Chen, Z. Li, M. Wang, and Y. Wei · 2024
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Unipc: A unified predictor-corrector framework for fast sampling of diffusion models
W. Zhao, L. Bai, Y. Rao, J. Zhou, and J. Lu · 2024
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