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molecular-property-prediction-on

Atomistic DescriptionMolecular Property Prediction
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PaperCodeRMSEModelNameReleaseDate
Uni-Mol: A Universal 3D Molecular Representation Learning Framework✓ Link0.603Uni-Mol2022-09-08
Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning✓ Link0.609SMA2024-02-22
ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction0.66ChemRL-GEM2021-06-11
Analyzing Learned Molecular Representations for Property Prediction✓ Link0.683D-MPNN2019-04-02
Bidirectional Generation of Structure and Properties Through a Single Molecular Foundation Model✓ Link0.706SPMM2022-11-19
Strategies for Pre-training Graph Neural Networks✓ Link0.739PretrainGNN2019-05-29
A Bayesian Flow Network Framework for Chemistry Tasks✓ Link0.746ChemBFN2024-07-28
Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck✓ Link0.762±0.042S-CGIB2025-02-20
ChemBERTa-2: Towards Chemical Foundation Models✓ Link0.798ChemBERTa-2 (MTR-77M)2022-09-05
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules✓ Link0.812N-GramRF2018-06-24
Self-Supervised Graph Transformer on Large-Scale Molecular Data✓ Link0.817GROVER (base)2020-06-18
Self-Supervised Graph Transformer on Large-Scale Molecular Data✓ Link0.823GROVER (large)2020-06-18
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules✓ Link2.072N-GramXGB2018-06-24
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