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ResearchFormerly WizWand

Molecular Property Prediction on MoleculeNet ClinTox (scaffold)

0.983ROC-AUCChem-GMNet
0.323640.494820.6660.83718May 29, 2019Jul 25, 2020Sep 22, 2021Nov 19, 2022Jan 17, 2024Mar 15, 2025May 13, 2026
Updated 5mo ago

Evaluation results

MethodLinks
Chem-GMNetPre-trained=true, Pre-training Corpus=10M SMILES, Pre-training Task=MLM-10M2026.050.983
DumplingGNN2024.090.959
SYN-FUSIONfusion_source=MolCLR2023.080.947
SYN-FUSIONfusion_source=Hu et. al2023.080.946
MolXPT2024.090.919
GEM2024.090.912
D-MPNN2024.090.906
D-MPNN2023.080.905
Uni-Mol2024.090.901
MolCLRbackbone=GIN2023.080.886
N-Gram XGBClassifier=XGBoost2024.090.875
PretrainGNN2024.090.875
Attentive FP2024.090.832
MolCLR2024.090.791
Hu et al.2023.080.789
GTOT-TuningBackbone=GIN (supervised_contextpred), Strategy=GTOT-Tuning2022.030.779
N-Gram RFClassifier=Random Forest2024.090.775
GraphMVP2024.090.762
GINGraph-level pre-training=Supervised, Node-level pre-training=Attribute Masking2019.050.737
BSSBackbone=GIN (supervised_contextpred), Strategy=Fine-tuning strategy2022.030.737
StochNormBackbone=GIN (supervised_contextpred), Strategy=Fine-tuning strategy2022.030.732
DELTABackbone=GIN (supervised_contextpred), Strategy=Fine-tuning strategy2022.030.727
Feature (DELTA w/o ATT)Backbone=GIN (supervised_contextpred), Strategy=Fine-tuning strategy2022.030.727
GROVER_largeModel scale=large2024.090.726
GINGraph-level pre-training=Supervised, Node-level pre-training=Context Prediction2019.050.726
Fine-TuningBackbone=GIN (supervised_contextpred), Strategy=Baseline2022.030.726
GINGraph-level pre-training=None, Node-level pre-training=Attribute Masking2019.050.718
L2_SPBackbone=GIN (supervised_contextpred), Strategy=Fine-tuning strategy2022.030.718
RF2023.080.713
GINGraph-level pre-training=Supervised, Node-level pre-training=Infomax2019.050.712
GINGraph-level pre-training=Supervised, Node-level pre-training=EdgePred2019.050.709
GINGraph-level pre-training=None, Node-level pre-training=Infomax2019.050.699
SVM2023.080.669
GINGraph-level pre-training=None, Node-level pre-training=Context Prediction2019.050.659
NID_CLEvaluation Protocol=Linear Probing, Pre-training Dataset=ZINC15, Backbone=5-layer GIN2024.050.653
GINGraph-level pre-training=None, Node-level pre-training=EdgePred2019.050.641
SimGRACEEvaluation Protocol=Linear Probing, Pre-training Dataset=ZINC15, Backbone=5-layer GIN2024.050.634
GCN2023.080.625
GraphCLEvaluation Protocol=Linear Probing, Pre-training Dataset=ZINC15, Backbone=5-layer GIN2024.050.598
GIN2023.080.58
GINGraph-level pre-training=None, Node-level pre-training=None2019.050.58
GINGraph-level pre-training=Supervised, Node-level pre-training=None2019.050.572
JOAOEvaluation Protocol=Linear Probing, Pre-training Dataset=ZINC15, Backbone=5-layer GIN2024.050.541
AttrMaskEvaluation Protocol=Linear Probing, Pre-training Dataset=ZINC15, Backbone=5-layer GIN2024.050.516
EdgePredEvaluation Protocol=Linear Probing, Pre-training Dataset=ZINC15, Backbone=5-layer GIN2024.050.489
ContextPredEvaluation Protocol=Linear Probing, Pre-training Dataset=ZINC15, Backbone=5-layer GIN2024.050.432
ChemBERTa-2Pre-trained=true, Pre-training Corpus=10M SMILES, Pre-training Task=MLM-10M2026.050.349