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Formation Energy On Materials Project

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MAE

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このベンチマークにおける各モデルのパフォーマンス結果

モデル名
MAE
Paper TitleRepository
Matformer21.2Periodic Graph Transformers for Crystal Material Property Prediction
SchNet35SchNet - a deep learning architecture for molecules and materials
PotNet18.8Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction
MEGNet28Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals
SchNet31.8Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials
CGCNN39Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties
CartNet17.47A Cartesian Encoding Graph Neural Network for Crystal Structures Property Prediction: Application to Thermal Ellipsoid Estimation
MT-CGCNN41MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction
SchNet-edge-update22.7Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials
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