score_sde
minDiffusion
| score_sde | minDiffusion | |
|---|---|---|
| 6 | 2 | |
| 1,242 | 684 | |
| - | - | |
| 0.0 | 0.0 | |
| over 1 year ago | almost 2 years ago | |
| Jupyter Notebook | Python | |
| Apache License 2.0 | - |
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score_sde
- Ask HN: How to get back into AI?
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[D] Variance of sampling in diffusion models
Perhaps the ODE interpretation would be helpful (see here and here) which turns DDPMs into neural ODEs using the Fokker-Planck equation so after the initial starting noise, the sampling process is deterministic. If samples are noisy even with the full number of steps then you might need to increase the number of steps further.
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[D] Why is the diffution model so powerful? but the math behind it is so simple.
Turns out that diffusion models also define a certain differential equation, making it a neural ODE. Then you can just integrate the ODE in the other direction to get the exact inverse for the DDPM (it's not entirely exact b/c of numerical error in the solver, but close enough)
- [D] Are DDPMs a variation on Score Based Generative Modeling? Or is there a fundemental difference between the two?
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Diffusion Models Beat GANs on Image Synthesis
This new approach to generative modelling looks very intriguing.
In a similar ilk, there's this ICLR paper from this year using stochastic differential equations for generative modelling: https://arxiv.org/abs/2011.13456
- [D] Efficient, concurrent input pipelines in JAX?
minDiffusion
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[D] Why is the diffution model so powerful? but the math behind it is so simple.
You can see the 200 lines code here: https://nn.labml.ai/diffusion/ddpm/index.html and https://github.com/cloneofsimo/minDiffusion, math is here: https://lilianweng.github.io/posts/2021-07-11-diffusion-models/
- [P] Extremely short and simple implementation of Denoising Diffusion Model, for educational purpose
What are some alternatives?
guided-diffusion
fish-diffusion - An easy to understand TTS / SVS / SVC framework
pytorch-generative - Easy generative modeling in PyTorch.
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
SDE - Example codes for the book Applied Stochastic Differential Equations
stable-diffusion-webui - Stable Diffusion web UI
Financial-Models-Numerical-Methods - Collection of notebooks about quantitative finance, with interactive python code.
stable-diffusion-docker - Run the official Stable Diffusion releases in a Docker container with txt2img, img2img, depth2img, pix2pix, upscale4x, and inpaint.
Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch - [ECCV 2022] Compositional Generation using Diffusion Models
peft - 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
score_sde_pytorch - PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)