تقرير
Geometric Deep Learning: a Temperature Based Analysis of Graph Neural Networks
| العنوان: | Geometric Deep Learning: a Temperature Based Analysis of Graph Neural Networks |
|---|---|
| المؤلفون: | Lapenna, M., Faglioni, F., Zanchetta, F., Fioresi, R. |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Machine Learning, Computer Science - Artificial Intelligence |
| الوصف: | We examine a Geometric Deep Learning model as a thermodynamic system treating the weights as non-quantum and non-relativistic particles. We employ the notion of temperature previously defined in [7] and study it in the various layers for GCN and GAT models. Potential future applications of our findings are discussed. Comment: Published on Proceedings of GSI 2023 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2309.00699 |
| رقم الأكسشن: | edsarx.2309.00699 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |