Diffusion Explorer: Interactive Exploration of Diffusion Models
On the map: Diffusion models → Diffusion foundations and sampling
Abstract (arXiv)
Diffusion models have been central to the development of recent image, video, and even text generation systems. They posses striking geometric properties that can be faithfully portrayed in low-dimensional settings. However, existing resources for explaining diffusion either require an advanced theoretical foundation or focus on their neural network architectures rather than their rich geometric properties. We introduce Diffusion Explorer, an interactive tool to explain the geometric properties of diffusion models. Users can train 2D diffusion models in the browser and observe the temporal dynamics of their sampling process. Diffusion Explorer leverages interactive animation, which has been shown to be a powerful tool for making engaging visualizations of dynamic systems, making it well suited to explaining diffusion models which represent stochastic processes that evolve over time. Diffusion Explorer is open source and a live demo is available at alechelbling.com/Diffusion-Explorer.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Diffusion foundations and sampling, one of 14 directions in Diffusion models. Builds on 3 of its 8 references that are in the map. First posted on arXiv 1 Jul 2025.
Builds on
3 of 8 references.
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Same direction, newest first
- 2020Denoising Diffusion Probabilistic Models19 Jun
Other references · 2
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Citing papers per year: 2026: 1.
1 paper.
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Close in wording, no citation either way
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