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SOTA
Moleküleigenschaftsvorhersage
Molecular Property Prediction On Bbbp 1
Molecular Property Prediction On Bbbp 1
Metriken
ROC-AUC
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
ROC-AUC
Paper Title
DumplingGNN
96.4
Dumpling GNN: Hybrid GNN Enables Better ADC Payload Activity Prediction Based on Chemical Structure
ChemBFN
95.74
A Bayesian Flow Network Framework for Chemistry Tasks
MTL-BERT
93.0
Pushing the boundaries of molecular property prediction for drug discovery with multitask learning BERT enhanced by SMILES enumeration
XGBoost
90.5
Accurate ADMET Prediction with XGBoost
SELFormer
90.2
SELFormer: Molecular Representation Learning via SELFIES Language Models
STL-BERT
89.6
Pushing the boundaries of molecular property prediction for drug discovery with multitask learning BERT enhanced by SMILES enumeration
Cano-BERT
89.2
Pushing the boundaries of molecular property prediction for drug discovery with multitask learning BERT enhanced by SMILES enumeration
AttrMasking
89.2
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development
S-CGIB
88.75±0.49
Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck
AttentiveFP
85.5
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development
MolXPT
80.5 ± 0.5
MolXPT: Wrapping Molecules with Text for Generative Pre-training
Deep-CBN
75.8
Integrating convolutional layers and biformer network with forward-forward and backpropagation training
SMA
75.0
Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning
SPMM
73.3
Bidirectional Generation of Structure and Properties Through a Single Molecular Foundation Model
Uni-Mol
72.9
Uni-Mol: A Universal 3D Molecular Representation Learning Framework
Uni-Mol
72.9
Galactica: A Large Language Model for Science
ChemBERTa-2 (MTR-77M)
72.8
ChemBERTa-2: Towards Chemical Foundation Models
ChemRL-GEM
72.4
ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction
D-MPNN
71.0
Analyzing Learned Molecular Representations for Property Prediction
GROVER (base)
70.0
Self-Supervised Graph Transformer on Large-Scale Molecular Data
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Molecular Property Prediction On Bbbp 1 | SOTA | HyperAI