Formation Energy On Materials Project

المقاييس

MAE

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

		Paper Title
MT-CGCNN	41	MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction
CGCNN	39	Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties
SchNet	35	SchNet - a deep learning architecture for molecules and materials
SchNet	31.8	Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials
MEGNet	28	Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals
SchNet-edge-update	22.7	Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials
Matformer	21.2	Periodic Graph Transformers for Crystal Material Property Prediction
PotNet	18.8	Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction
CartNet	17.47	A Cartesian Encoding Graph Neural Network for Crystal Structures Property Prediction: Application to Thermal Ellipsoid Estimation

0 of 9 row(s) selected.

Formation Energy On Materials Project | SOTA | HyperAI