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<h1 align='center'>sbgm</h1>
<h2 align='center'>Score-Based Diffusion Models in JAX</h2>

Implementation and extension of
* [Score-Based Generative Modeling through Stochastic Differential Equations (Song++20)](https://arxiv.org/abs/2011.13456)
Implementation and extension of [Score-Based Generative Modeling through Stochastic Differential Equations (Song++20)](https://arxiv.org/abs/2011.13456) and [Maximum Likelihood Training of Score-Based Diffusion Models (Song++21)](https://arxiv.org/abs/2101.09258) in `jax` and `equinox`.

and

* [Maximum Likelihood Training of Score-Based Diffusion Models (Song++21)](https://arxiv.org/abs/2101.09258)

in `jax` and `equinox`.
This repository provides a lightweight library of models, sampling and likelihood routines. Suitable for likelihood-free or emulation based approaches. Tested and typed code to ensure reliable benchmarkable training and inference.

> [!WARNING]
> :building_construction: Note this repository is under construction, expect changes. :building_construction:
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<p align="center">
<img src="https://github.com/homerjed/sbgm/blob/main/figs/score.png" />
<img src="https://github.com/homerjed/sbgm/blob/main/assets/score.png" />
</p>

*A diagram (see citations) showing how to map data to a noise distribution (the prior) with an SDE, and reverse this SDE for generative modeling. One can also reverse the associated probability flow ODE, which yields a deterministic process that samples from the same distribution as the SDE. Both the reverse-time SDE and probability flow ODE can be obtained by estimating the score.*
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<h4 align='left'>Flowers</h4>

Euler-Marayama sampling
![Flowers Euler-Marayama sampling](figs/flowers_eu.png?raw=true)
![Flowers Euler-Marayama sampling](assets/flowers_eu.png?raw=true)

ODE sampling
![Flowers ODE sampling](figs/flowers_ode.png?raw=true)
![Flowers ODE sampling](assets/flowers_ode.png?raw=true)

<h4 align='left'>CIFAR10</h4>

Euler-Marayama sampling
![CIFAR10 Euler-marayama sampling](figs/cifar10_eu.png?raw=true)
![CIFAR10 Euler-marayama sampling](assets/cifar10_eu.png?raw=true)

ODE sampling
![CIFAR10 ODE sampling](figs/cifar10_ode.png?raw=true)
![CIFAR10 ODE sampling](assets/cifar10_ode.png?raw=true)

<!-- ![alt text](figs/flowers_ode.png?raw=true) -->
<!-- ![alt text](assets/flowers_ode.png?raw=true) -->

### SDEs
![alt text](figs/sdes.png?raw=true)
![alt text](assets/sdes.png?raw=true)

### Citations
```bibtex
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