Molecular Property Prediction On Sider 1

Métriques

ROC-AUC

Résultats

Résultats de performance de divers modèles sur ce benchmark

		Paper Title
BioAct-Het	91.11	BioAct-Het: A Heterogeneous Siamese Neural Network for Bioactivity Prediction Using Novel Bioactivity Representatio
Deep-CBN	78.2	Integrating convolutional layers and biformer network with forward-forward and backpropagation training
MolXPT	71.7	MolXPT: Wrapping Molecules with Text for Generative Pre-training
IterRefLSTM	70.40	Low Data Drug Discovery with One-shot Learning
ChemRL-GEM	67.2	ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction
N-GramRF	66.8	N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules
Uni-Mol	65.9	Uni-Mol: A Universal 3D Molecular Representation Learning Framework
N-GramXGB	65.5	N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules
GROVER (large)	65.4	Self-Supervised Graph Transformer on Large-Scale Molecular Data
GROVER (base)	64.8	Self-Supervised Graph Transformer on Large-Scale Molecular Data
SPMM	64.7	Bidirectional Generation of Structure and Properties Through a Single Molecular Foundation Model
S-CGIB	64.03±1.04	Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck
GAL 120B	63.2	Galactica: A Large Language Model for Science
PretrainGNN	62.7	Strategies for Pre-training Graph Neural Networks
GAL 30B	61.3	Galactica: A Large Language Model for Science
D-MPNN	57.0	Analyzing Learned Molecular Representations for Property Prediction
GAL 125M	55.9	Galactica: A Large Language Model for Science
GAL 6.7B	55.9	Galactica: A Large Language Model for Science
GAL 1.3B	54.0	Galactica: A Large Language Model for Science

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Molecular Property Prediction On Sider 1 | SOTA | HyperAI