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  4. Drug Discovery On Qm9

Drug Discovery On Qm9

评估指标

Error ratio

评测结果

各个模型在此基准测试上的表现结果

模型名称
Error ratio
Paper TitleRepository
PaiNN0.411Equivariant message passing for the prediction of tensorial properties and molecular spectra-
Gated Graph Sequence NN1.36Gated Graph Sequence Neural Networks-
DimeNet++0.410Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules-
ComENet0.403ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs-
PAMNet0.363A Universal Framework for Accurate and Efficient Geometric Deep Learning of Molecular Systems
MPNNs0.68Neural Message Passing for Quantum Chemistry-
Molecular Graph Convolutions2.59Molecular Graph Convolutions: Moving Beyond Fingerprints-
SphereNet0.386Spherical Message Passing for 3D Graph Networks-
DeepMoleNet0.531Transferable Multi-level Attention Neural Network for Accurate Prediction of Quantum Chemistry Properties via Multi-task Learning-
MXMNet0.382Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures-
DimeNet0.44Directional Message Passing for Molecular Graphs-
0 of 11 row(s) selected.
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