SOTAVerified

Molecular Property Prediction

Molecular property prediction is the task of predicting the properties of a molecule from its structure.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–10 of 354 papers

TitleStatusHype
Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures—0
Combining Graph Neural Networks and Mixed Integer Linear Programming for Molecular Inference under the Two-Layered Model—0
TRIDENT: Tri-Modal Molecular Representation Learning with Taxonomic Annotations and Local Correspondence—0
Descriptor-based Foundation Models for Molecular Property PredictionCode2
Robust Molecular Property Prediction via Densifying Scarce Labeled DataCode0
BioLangFusion: Multimodal Fusion of DNA, mRNA, and Protein Language Models—0
The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine LearningCode0
Graph Neural Networks in Modern AI-aided Drug Discovery—0
Recent Developments in GNNs for Drug Discovery—0
AdaptMol: Adaptive Fusion from Sequence String to Topological Structure for Few-shot Drug Discovery—0
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All datasetsBBBPBACESIDERTox21clintoxLipophilicityFreeSolvHIV datasetESOLQM7QM8QM9

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DVMPAUC0.81—Unverified
2Uni-MolAUC0.81—Unverified
3ChemBFNAUC0.79—Unverified
4ChemBERTa-2 Fine-tunedAUC0.79—Unverified
5SMAAUC0.79—Unverified
6MolXPTAUC0.78—Unverified
7GAL 30BAUC0.76—Unverified
8GAL 120BAUC0.75—Unverified
9GAL 1.3BAUC0.72—Unverified
10GAL 6.7BAUC0.72—Unverified