PIDM
score_sde_pytorch
| PIDM | score_sde_pytorch | |
|---|---|---|
| 1 | 4 | |
| 457 | 1,401 | |
| - | - | |
| 6.2 | 0.0 | |
| 2 months ago | over 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
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PIDM
score_sde_pytorch
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[D] score based vs. Diffusion models
there's an implementation of score-based models from the paper that showed how score based models and diffusion models are the same here: https://github.com/yang-song/score_sde_pytorch
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Machine learning and black box numerical solver[D]
Someone has already mentioned Neural Ordinary Differential Equations, which is also the first thing that came to mind. There are also extensions to it, where one can use PDEs(Neural Hamiltonian Flows) or even stochastic DEs(Score-Based Generative Models) in the model. All of them covering different but overlapping use cases.
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[Discussion] Could someone explain the math behind the number of distinct images that can be generated with a latent diffusion model?
I was considering an unconditional latent diffusion model, but for conditional models, the computation becomes much more complex (we might have to use bayes here). If we use Score-Based Generative Modeling (https://arxiv.org/abs/2011.13456), we could try to find and count all the unique local minima and saddle points, but it is not clear how we can do this...
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[D] Machine Learning - WAYR (What Are You Reading) - Week 138
You can find an implementation here: https://github.com/yang-song/score_sde_pytorch/blob/main/models/ddpm.py
What are some alternatives?
dpm-solver - Official code for "DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps" (Neurips 2022 Oral)
Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch - [ECCV 2022] Compositional Generation using Diffusion Models
diffusion_models - Minimal standalone example of diffusion model
score_sde - Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Magic123 - [ICLR24] Official PyTorch Implementation of Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors
DiffusionFastForward - DiffusionFastForward: a free course and experimental framework for diffusion-based generative models
Self-Attention-Guidance - Official implementation of the paper "Improving Sample Quality of Diffusion Models Using Self-Attention Guidance" (ICCV 2023)