Awesome-Diffusion-Models
A collection of resources and papers on Diffusion Models
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Decision brief
Curated Diffusion Models resources including academic papers, tutorials, and overviews across various applications.
Good fit when
- Need a comprehensive overview of Diffusion Model-related research across vision, audio, NLP, and more
- Seeking introductory materials like posts, papers, videos for foundational understanding
Avoid when
- If you require highly specialized or application-specific tools rather than resources汇集。
- That demand interactive workshops or real-time tutorials instead of static resource listings
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (730d since push)
- As of 2w
- Provenance
- Not a fork · Personal account
- As of 2w
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- As of 1mo
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git clone https://github.com/diff-usion/Awesome-Diffusion-ModelsHow it fits your stack(1)
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
This repository serves as a curated list of academic papers, tutorials, and other resources related to diffusion models, spanning various applications such as vision, audio, natural language processing, reinforcement learning, and more.
Capability facts
- Languages
- html
Source: github.language · Aug 1, 2026
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README
This repository contains a collection of resources and papers on Diffusion Models.
Please refer to this page as this page may not contain all the information due to page constraints.
Contents
- Resources
- Introductory Posts
- Introductory Papers
- Introductory Videos
- Introductory Lectures
- Tutorial and Jupyter Notebook
- Papers
- Survey
- Vision
- Generation
- Classification
- Segmentation
- Image Translation
- Inverse Problems
- Medical Imaging
- Multi-modal Learning
- 3D Vision
- Adversarial Attack
- Miscellany
- Audio
- Generation
- Conversion
- Enhancement
- Separation
- Text-to-Speech
- Miscellany
- Natural Language
- Tabular and Time Series
- Generation
- Forecasting
- Imputation
- Miscellany
- Graph
- Generation
- Molecular and Material Generation
- Reinforcement Learning
- Theory
- Applications
Resources
Introductory Posts
:fast_forward: DiffusionFastForward: 01-Diffusion-Theory
Mikolaj Czerkawski (@mikonvergence)
[Website]
4 Feb 2023
How diffusion models work: the math from scratch
Sergios Karagiannakos,Nikolas Adaloglou
[Website]
24 Sep 2022
A Path to the Variational Diffusion Loss
Alex Alemi
[Website] [Colab]
15 Sep 2022
The Annotated Diffusion Model
Niels Rogge, Kashif Rasul
[Website]
06 Jun 2022
The recent rise of diffusion-based models
Maciej Domagała
[Website]
06 Jun 2022
Introduction to Diffusion Models for Machine Learning
Ryan O'Connor
[Website]
12 May 2022
Improving Diffusion Models as an Alternative To GANs
Arash Vahdat and Karsten Kreis
[Website-Part 1] [Website-Part 2]
26 Apr 2022
An introduction to Diffusion Probabilistic Models
Ayan Das
[Website]
04 Dec 2021
Introduction to deep generative modeling: Diffusion-based Deep Generative Models
Jakub Tomczak
[Website]
30 Aug 2021
What are Diffusion Models?
Lilian Weng
[Website]
11 Jul 2021
Diffusion Models as a kind of VAE
Angus Turner
[[Website](https://angusturner.github.io/generative_models/2021/06/29/diffusion-probabilistic-models-I.ht
For agents
This page has a .md twin and JSON over the API.