SOTAVerified

Molecular Property Prediction

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

Papers

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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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Deep-CBNROC-AUC92.4—Unverified
2BioAct-HetROC-AUC89.8—Unverified
3IterRefLSTMROC-AUC83—Unverified
4Uni-MolROC-AUC79.6—Unverified
5ChemRL-GEMROC-AUC78.1—Unverified
6PretrainGNNROC-AUC78.1—Unverified
7AutogluonROC-AUC77.84—Unverified
8MolXPTROC-AUC77.1—Unverified
9D-MPNNROC-AUC75.9—Unverified
10N-GramXGBROC-AUC75.8—Unverified