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Similarity-based pairing improves efficiency of siamese neural networks for regression tasks and uncertainty quantification
Siamese networks, representing a novel class of neural networks, consist of two identical subnetworks sharing weights but receiving different inputs. Here we present a similarity-based pairing method for generating compound pairs to train Siamese neural networks for regression tasks. In comparison w...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10469421/ https://www.ncbi.nlm.nih.gov/pubmed/37649050 http://dx.doi.org/10.1186/s13321-023-00744-6 |