Diffusion model/score-matching chronology
- Estimation of Non-Normalized Statistical Models by Score Matching, Hyvarinen (2005)
- Bayesian Learning via Stochastic Gradient Langevin Dynamics, Welling & Teh (2011)
- A connection between score matching and denoising autoencoders, Vincent (2011)
- Interpretation and Generalization of Score Matching, Lyu (2012)
- Deep Unsupervised Learning using Nonequilibrium Thermodynamics, Sohl-Dickstein (2015)
- Deep Energy Estimator Networks, Saremi (2018)
- Generating Diverse High-Fidelity Images with VQ-VAE-2, Razavi et al (2019)
- Generative Modeling by Estimating Gradients of the Data Distribution, Song & Ermon (2019)
- Sliced Score Matching: A Scalable Approach to Density and Score Estimation, Song et al., (2019)
- Efficient learning of generative models via finite-difference score matching, Pang et al (2020)
- Scaling Laws for Autoregressive Generative Modeling, Henighan et al (2020)
- Improved Techniques for Training Score-Based Generative Models, Song & Ermon (2020)
- Denoising Diffusion Probabilistic Models, Ho et al. (2020)
- Score-Based Generative Modeling through Stochastic Differential Equations, Song et al. (2020)
- Denoising Diffusion Implicit Models, Song (different Song!) et al. (2020)
- Variational Diffusion Models, Kingma et al (2021)
- Improved Denoising Diffusion Probabilistic Models, Nichol & Dhariwal (2021)
- Maximum Likelihood Training of Score-Based Diffusion Models, Song et al (2021)
- Scalable Diffusion Models with Transformers, Peebles et al (2022)
- Progressive Distillation for Fast Sampling of Diffusion Models, Salimans & Ho (2022)
- Elucidating the Design Space of Diffusion-Based Generative Models, Karras et al (2022)
- Analyzing and Improving the Training Dynamics of Diffusion Models, Karras et al (2023)
- Generalization in diffusion models arises from geometry-adaptive harmonic representations, Kadkhodaie et al (2024)
- Rolling Diffusion Models, Ruhe et al (2024)
Pedagogical & reviews on diffusion, VAE