Скачать или смотреть Interactive Guide: Flow and Diffusion - Free GitHub Workbook

Ever wondered how AI art generators like Stable Diffusion or Midjourney transform simple noise into stunning images? The magic lies in powerful generative modeling techniques like Flow Matching and Diffusion Models. In this video, we break down these complex concepts with a fully interactive, hands-on simulation!

Go from zero to hero as we explore the core mathematics behind these state-of-the-art models. You'll learn how they use Ordinary and Stochastic Differential Equations (ODEs & SDEs) to create a "flow" that guides random pixels into coherent, masterpiece-level art.

🚀 In This Interactive Tutorial, You Will:

Visualize the Process: See how a cloud of random noise gets sculpted into a target shape right before your eyes.

Toggle Between Methods: Switch between deterministic Flow Matching (ODEs) and stochastic Diffusion (SDEs) to understand their unique behaviors.

Explore the Math: Dive into the step-by-step mathematical phases, from creating noisy samples to calculating vector fields and score functions.

Understand p_data: Learn why the underlying data distribution is key to the entire process.

Bridge Theory and Practice: See high-level Python code examples that show how these concepts are implemented in frameworks like PyTorch.

This isn't just a lecture; it's an interactive journey into the heart of modern generative AI. Perfect for students, developers, and anyone curious about the engine driving the creative AI revolution.

📚 Source Materials & Further Reading:
This interactive tutorial is heavily based on the phenomenal course notes from MIT's "Generative AI With Stochastic Differential Equations." We highly recommend diving deeper with the source material.

MIT Course Lecture Notes:
diffusion.csail.mit.edu/docs/lecture-notes.pdf

GitHub Repository with Tutorial Code & Concepts:
github.com/Ebayednoob/Neural-Symbolic-AI/tree/main/Developments/Papers-Tutorials/Flow%20and%20Diffusion

#️⃣ Tags:
#DiffusionModels #FlowMatching #GenerativeAI #MachineLearning #AI #ArtificialIntelligence #StableDiffusion #DataScience #PyTorch #Tutorial