Summary of Cleandiffuser: An Easy-to-use Modularized Library For Diffusion Models in Decision Making, by Zibin Dong et al.
CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Making
by Zibin Dong, Yifu Yuan, Jianye Hao, Fei Ni, Yi Ma, Pengyi Li, Yan Zheng
First submitted to arxiv on: 13 Jun 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Machine Learning (cs.LG); Robotics (cs.RO)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The authors introduce CleanDiffuser, an open-source library for building decision-making agents using diffusion models (DMs). They identify essential sub-modules that constitute the core of the library, allowing for the implementation of various DM algorithms with simple and flexible building blocks. The library is designed to be easy to use and modularized, making it ideal for developers who want to build customized DM-based decision-making algorithms. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary CleanDiffuser is a new open-source library that helps people build smart decision-making agents using powerful computer models called diffusion models. These models are really good at generating data that looks like real data. The authors of CleanDiffuser made it easy to use and broke it down into smaller pieces, so developers can pick the parts they need to make their own smart decision-making tools. |
Keywords
* Artificial intelligence * Diffusion
