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SOTA
Drug Discovery
Drug Discovery On Tox21
Drug Discovery On Tox21
评估指标
AUC
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
AUC
Paper Title
Repository
ContextPred
0.781
Strategies for Pre-training Graph Neural Networks
-
GraphConv + dummy super node
0.854
Learning Graph-Level Representation for Drug Discovery
TrimNet
0.860
TrimNet: learning molecular representation from triplet messages for biomedicine
RNN-DFS
0.748
Relational Pooling for Graph Representations
GraphConv
0.846
Convolutional Networks on Graphs for Learning Molecular Fingerprints
Ensemble predictor
0.862
ToxicBlend: Virtual Screening of Toxic Compounds with Ensemble Predictors
-
elEmBERT-V1
0.961
Structure to Property: Chemical Element Embeddings and a Deep Learning Approach for Accurate Prediction of Chemical Properties
GIT-Mol(G+S)
0.759
GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and Text
SNN (SELU Network)
0.845
Self-Normalizing Neural Networks
SSVAE with multiple SMILES
0.871
All SMILES Variational Autoencoder
-
TrimNet + Perforated Backpropagation
0.885
Perforated Backpropagation: A Neuroscience Inspired Extension to Artificial Neural Networks
0 of 11 row(s) selected.
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