Fetching the paper…
Reading the bibliography…
Score-based generative modeling with probability flow ordinary differential equations (ODEs) has achieved remarkable success in a variety of applications.
Reverse-time diffusion equation models
B. D. O. Anderson · 1982
Earlier work this paper cites.
On choosing and bounding probability metrics
A. L. Gibbs and F. E. Su · 2002
Earlier work this paper cites.
Estimation of non-normalized statistical models by score matching
A. Hyvärinen and P. Dayan · 2005
Earlier work this paper cites.
Optimal Transport: Old and New
C. Villani · 2009
Earlier work this paper cites.
A connection between score matching and denoising autoencoders
P. Vincent · 2011
Earlier work this paper cites.
Analysis and Geometry of Markov Diffusion Operators
D. Bakry, I. Gentil, and M. Ledoux · 2014
Earlier work this paper cites.
Deep unsupervised learning using nonequilibrium thermodynamics
J. Sohl-Dickstein, E. Weiss, N. Maheswaranathan, and S. Ganguli · 2015
Earlier work this paper cites.
Reflection couplings and contraction rates for diffusions
A. Eberle · 2016
Earlier work this paper cites.
GANs trained by a two time-scale update rule converge to a local Nash equilibrium
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, and S. Hochreiter · 2017
Earlier work this paper cites.
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient
A. S. Dalalyan and A. G. Karagulyan · 2019
Earlier work this paper cites.
Generative modeling by estimating gradients of the data distribution
Y. Song and S. Ermon · 2019
Earlier work this paper cites.
Generative modeling with denoising auto-encoders and Langevin sampling
A. Block, Y. Mroueh, and A. Rakhlin · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
J. Ho, A. Jain, and P. Abbeel · 2020
Earlier work this paper cites.
Sliced score matching: A scalable approach to density and score estimation
Y. Song, S. Garg, J. Shi, and S. Ermon · 2020
Cited alongside, same era.
Diffusion Schrödinger bridge with applications to score-based generative modeling
V. De Bortoli, J. Thornton, J. Heng, and A. Doucet · 2021
Cited alongside, same era.
Decentralized stochastic gradient Langevin dynamics and Hamiltonian Monte Carlo
M. Gürbüzbalaban, X. Gao, Y. Hu, and L. Zhu · 2021
Cited alongside, same era.
Grad-TTS: A diffusion probabilistic model for text-to-speech
V. Popov, I. Vovk, V. Gogoryan, T. Sadekova, and M. Kudinov · 2021
Cited alongside, same era.
Score-based generative modeling through stochastic differential equations
Y. Song, J. Sohl-Dickstein, D. P. Kingma, A. Kumar, S. Ermon, and B. Poole · 2021
Cited alongside, same era.
Building normalizing flows with stochastic interpolants
S. Bruno, Y. Zhang, D.-Y. Lim, Ö. D. Akyildiz, and S. Sabanis · 2023
Later among the works it cites.
Time reversal of diffusion processes under a finite entropy condition
P. Cattiaux, G. Conforti, I. Gentil, and C. Léonard · 2023
Later among the works it cites.
Convergence of flow-based generative models via proximal gradient descent in Wasserstein space
X. Cheng, J. Lu, Y. Tan, and Y. Xie · 2023
Later among the works it cites.
Convergence of score-based generative modeling for general data distributions
H. Lee, J. Lu, and Y. Tan · 2023
Later among the works it cites.
Flow matching for generative modeling
Y. Lipman, R. T. Chen, H. Ben-Hamu, M. Nickel, and M. Le · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
M. S. Albergo and E. Vanden-Eijnden · 2022
Cited alongside, same era.
Convergence of denoising diffusion models under the manifold hypothesis
V. De Bortoli · 2022
Cited alongside, same era.
Elucidating the design space of diffusion-based generative models
T. Karras, M. Aittala, T. Aila, and S. Laine · 2022
Cited alongside, same era.
Convergence for score-based generative modeling with polynomial complexity
H. Lee, J. Lu, and Y. Tan · 2022
Cited alongside, same era.
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
Cited alongside, same era.
Hierarchical text-conditional image generation with CLIP latents
A. Ramesh, P. Dhariwal, A. Nichol, C. Chu, and M. Chen · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer · 2022
Cited alongside, same era.
Consistency models
Y. Song, P. Dhariwal, M. Chen, and I. Sutskever · 2023
Later among the works it cites.
Diffusion models: A comprehensive survey of methods and applications
L. Yang, Z. Zhang, Y. Song, S. Hong, R. Xu, Y. Zhao, Y. Shao, W. Zhang, B. Cui, and M.-H. Yang · 2023
Later among the works it cites.
Fast sampling of diffusion models with exponential integrator
Q. Zhang and Y. Chen · 2023
Later among the works it cites.
UniPC: A unified predictor-corrector framework for fast sampling of diffusion models
W. Zhao, L. Bai, Y. Rao, J. Zhou, and J. Lu · 2023
Later among the works it cites.
The blessing of randomness: SDE beats ODE in general diffusion-based image editing
S. Nie, H. A. Guo, C. Lu, Y. Zhou, C. Zheng, and C. Li · 2024
Closest in time.
Contractive diffusion probabilistic models
W. Tang and H. Zhao · 2024
Closest in time.
Wasserstein convergence guarantees for a general class of score-based generative models
X. Gao, H. M. Nguyen, and L. Zhu · 2025
Closest in time.