[Lipman et al. 2023] Flow Matching for Generative Modelling

[Sohl-Dickstein et al. 2015] Deep Unsupervised Learning using Nonequilibrium Thermodynamics

[Ho et al., NeurIPS 2020] Denoising Diffusion Probabilistic Models

[Song et al. UAI 2020] Sliced Score Matching: A Scalable Approach to Density and Score Estimation

[Song et al. NeurIPS 2019] Generative modeling by estimating gradients of the data distribution

[Song et al. ICLR 2021] Score-Based Generative Modeling through Stochastic Differential Equations

[Song et al. NeurIPS 2021] Maximum Likelihood Training of Score-Based Diffusion Models

Consistency Models

[Karras et al, NeurIPS 2022] Elucidating the Design Space of Diffusion-Based Generative Models (EDM)

Diffusion Models for Inverse Problems