Drug Discovery On Qm9

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Error ratio

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

		Paper Title
Molecular Graph Convolutions	2.59	Molecular Graph Convolutions: Moving Beyond Fingerprints
Gated Graph Sequence NN	1.36	Gated Graph Sequence Neural Networks
MPNNs	0.68	Neural Message Passing for Quantum Chemistry
DeepMoleNet	0.531	Transferable Multi-level Attention Neural Network for Accurate Prediction of Quantum Chemistry Properties via Multi-task Learning
DimeNet	0.44	Directional Message Passing for Molecular Graphs
PaiNN	0.411	Equivariant message passing for the prediction of tensorial properties and molecular spectra
DimeNet++	0.410	Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules
ComENet	0.403	ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs
SphereNet	0.386	Spherical Message Passing for 3D Graph Networks
MXMNet	0.382	Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures
PAMNet	0.363	A Universal Framework for Accurate and Efficient Geometric Deep Learning of Molecular Systems

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Drug Discovery On Qm9 | SOTA | HyperAI