Работы, цитирующие эту работу

Работ: 2

Работа: Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space

1. GrapheNet: a deep learning framework for predicting the physical and electronic properties of nanographenes using images

   Tommaso Forni, Matteo Baldoni, Fabio Le Piane +1

   СтатьяMachine Learning in Materials ScienceScientific Reports2024Цитирований: 0

   ABIABI:AkademIndex/openalex/2024.article.001036

2. Accurate classification of materials with elEmBERT: Element embeddings for chemical benchmarks

   Shokirbek Shermukhamedov, Dilorom Mamurjonova, Michael Probst

   СтатьяMachine Learning in Materials ScienceAPL Machine Learning2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.002993