Скачать или смотреть Pseudo Numerical Methods for Diffusion Models 🧠 | Fast Sampler Implementation in PyTorch

In this video, we dive into the paper "Pseudo Numerical Methods for Diffusion Models on Manifolds", introducing PNDM — one of the earliest fast sampling techniques for diffusion models. Learn how this method accelerates sampling while maintaining high fidelity, and follow along as we build it from scratch in PyTorch.

📘 What you’ll learn:

What PNDM is and how it works

The key ideas behind pseudo numerical solvers

How PNDM improves sampling over DDPM

Step-by-step implementation in PyTorch

How PNDM relates to tools like Stable Diffusion and Latent Diffusion Models

📄Link to the paper: https://arxiv.org/abs/2202.09778
GitHub: https://github.com/MaximeVandegar/Pap...
Udemy course: https://www.udemy.com/course/diffusio...

🛠️ This video is perfect for:

AI/ML students exploring diffusion-based generative models

Developers implementing fast samplers for image generation

Researchers interested in numerical methods for deep generative modeling


If you've ever searched for:

"What is PNDM?"

"Fast samplers for diffusion models"

"Implement PNDM in PyTorch"

"DDPM sampling alternatives"

"How Stable Diffusion sampling works"

Then this is the video for you!

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