OpenCodePapers

formation-energy-on-materials-project

Atomistic DescriptionFormation Energy
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PaperCodeMAEModelNameReleaseDate
A Cartesian Encoding Graph Neural Network for Crystal Structures Property Prediction: Application to Thermal Ellipsoid Estimation✓ Link17.47CartNet2025-01-30
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction✓ Link18.8PotNet2023-06-12
Periodic Graph Transformers for Crystal Material Property Prediction✓ Link21.2Matformer2022-09-23
Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials✓ Link22.7SchNet-edge-update2018-06-08
Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals✓ Link28MEGNet2018-12-12
Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials✓ Link31.8SchNet2018-06-08
SchNet - a deep learning architecture for molecules and materials✓ Link35SchNet2017-12-17
Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties✓ Link39CGCNN2017-10-27
MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction✓ Link41MT-CGCNN2018-11-14
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