Molecular Property Prediction On Qm8
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MAE
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이 벤치마크에서 각 모델의 성능 결과
모델 이름 | MAE | Paper Title | Repository |
|---|---|---|---|
| Uni-Mol | 0.0156 | Uni-Mol: A Universal 3D Molecular Representation Learning Framework | - |
| N-GramXGB | 0.0215 | N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules | |
| D-MPNN | 0.0190 | Analyzing Learned Molecular Representations for Property Prediction | |
| PretrainGNN | 0.0200 | Strategies for Pre-training Graph Neural Networks | |
| GROVER (large) | 0.0224 | Self-Supervised Graph Transformer on Large-Scale Molecular Data | |
| N-GramRF | 0.0236 | N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules | |
| GROVER (base) | 0.0218 | Self-Supervised Graph Transformer on Large-Scale Molecular Data | |
| ChemRL-GEM | 0.0171 | ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction | - |
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