Interaction without an interaction module
The prevailing way to model a many-body system is to encode every component and then let a module capture interaction. We show that the explicit interaction module is harmful when the number of components increases. We use a simple plastic encoder that compresses a component’s interaction contribution into its representation, and combine the representations by linear aggregation. This modelling approach is simple in form yet delivers unexpectedly excellent performance: it matches the prevailing explicit route under most conditions and exceeds it when a mixture carries more components than the training set covered. Moreover, an encoder produced this way has a clear advantage over per-component descriptors when it is transferred to a similar task: it greatly reduces the data requirements.
Authors
- Lingbo Ji
- Baojiang He (ORCID: https://orcid.org/0000-0002-5355-3296)
- Zhan Qu
- Xiao Yang (ORCID: https://orcid.org/0000-0002-0159-1434)
- Guanghao Song
- Xiankuan Huo
- Jun Hu
- Zihan Xu
- Feiyu Li
- Yanan Yang
Publication Details
- Journal
- ChemRxiv
- Published
- 2026-10-30
- DOI
- https://doi.org/10.26434/chemrxiv.15010330/v4
- Primary Topic
- Machine Learning in Materials Science
- Type
- preprint
Funders
- Tencent