Summary of Mdm: Molecular Diffusion Model For 3d Molecule Generation, by Lei Huang et al.
MDM: Molecular Diffusion Model for 3D Molecule Generation
by Lei Huang, Hengtong Zhang, Tingyang Xu, Ka-Chun Wong
First submitted to arxiv on: 13 Sep 2022
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Biomolecules (q-bio.BM)
GrooveSquid.com Paper Summaries
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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 In this paper, researchers tackle the challenge of generating three-dimensional molecular geometries from scratch, a crucial task in drug design. Current methods have limitations, particularly when creating large molecules or lacking diversity. To overcome these issues, the authors introduce a novel diffusion model that improves performance and diversity. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine you’re trying to create new medicines by designing tiny molecules. Right now, it’s hard to make them look like real molecules, especially big ones. The current way of doing this isn’t very good at making many different kinds of molecules. This paper suggests a new way to do it that makes it better. |
Keywords
* Artificial intelligence * Diffusion model
