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draft new ml-tech/discrete-diffusion post

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@ -259,28 +259,26 @@ Below are some preliminary results I obtained from a set of amorphous material g
![SDE shortcut results](sde-results.webp)
{% cap() %}Structural functions of generated materials, sampled in 10 steps.{% end %}
---
## References
1. Holderrieth and Erives, "An Introduction to Flow Matching and Diffusion Models."
2. Song and Ermon, "Generative Modeling by Estimating Gradients of the Data Distribution."
3. Rezende, Danilo, and Shakir Mohamed. "Variational inference with normalizing flows."
4. https://en.wikipedia.org/wiki/Differential_equation
5. https://en.wikipedia.org/wiki/Brownian_motion
6. https://en.wikipedia.org/wiki/Vector_field
7. https://en.wikipedia.org/wiki/Vector_flow
8. https://en.wikipedia.org/wiki/Ordinary_differential_equation
9. https://en.wikipedia.org/wiki/Stochastic_differential_equation
10. https://en.wikipedia.org/wiki/Euler_method
11. https://github.com/rtqichen/torchdiffeq
12. Lipman, Yaron, et al. "Flow matching for generative modeling."
13. Frans, Kevin, et al. "One step diffusion via shortcut models."
14. Geng, Zhengyang, et al. "Mean Flows for One-step Generative Modeling."
15. Liu, Xingchao, Chengyue Gong, and Qiang Liu. "Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow."
16. Ho, Jonathan, Ajay Jain, and Pieter Abbeel. "Denoising diffusion probabilistic models."
17. https://en.wikipedia.org/wiki/Diffusion_process
18. Huang et al., "Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion."
19. https://en.wikipedia.org/wiki/Euler–Maruyama_method
20. Song et al., "Score-Based Generative Modeling through Stochastic Differential Equations."
21. https://en.wikipedia.org/wiki/Informant_(statistics)
> **References:**
>
> 1. Holderrieth and Erives, "An Introduction to Flow Matching and Diffusion Models."
> 2. Song and Ermon, "Generative Modeling by Estimating Gradients of the Data Distribution."
> 3. Rezende, Danilo, and Shakir Mohamed. "Variational inference with normalizing flows."
> 4. https://en.wikipedia.org/wiki/Differential_equation
> 5. https://en.wikipedia.org/wiki/Brownian_motion
> 6. https://en.wikipedia.org/wiki/Vector_field
> 7. https://en.wikipedia.org/wiki/Vector_flow
> 8. https://en.wikipedia.org/wiki/Ordinary_differential_equation
> 9. https://en.wikipedia.org/wiki/Stochastic_differential_equation
> 10. https://en.wikipedia.org/wiki/Euler_method
> 11. https://github.com/rtqichen/torchdiffeq
> 12. Lipman, Yaron, et al. "Flow matching for generative modeling."
> 13. Frans, Kevin, et al. "One step diffusion via shortcut models."
> 14. Geng, Zhengyang, et al. "Mean Flows for One-step Generative Modeling."
> 15. Liu, Xingchao, Chengyue Gong, and Qiang Liu. "Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow."
> 16. Ho, Jonathan, Ajay Jain, and Pieter Abbeel. "Denoising diffusion probabilistic models."
> 17. https://en.wikipedia.org/wiki/Diffusion_process
> 18. Huang et al., "Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion."
> 19. https://en.wikipedia.org/wiki/Euler–Maruyama_method
> 20. Song et al., "Score-Based Generative Modeling through Stochastic Differential Equations."
> 21. https://en.wikipedia.org/wiki/Informant_(statistics)