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SOTA
Molecular Property Prediction
Molecular Property Prediction On Bace 1
Molecular Property Prediction On Bace 1
評価指標
ROC-AUC
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
Columns
モデル名
ROC-AUC
Paper Title
Repository
SMA
84.3
Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning
N-GramRF
77.9
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules
S-CGIB
86.46±0.81
Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck
ChemRL-GEM
85.6
ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction
-
GROVER (base)
82.6
Self-Supervised Graph Transformer on Large-Scale Molecular Data
ChemBERTa-2 (MTR-77M)
79.9
ChemBERTa-2: Towards Chemical Foundation Models
Uni-Mol
85.7
Uni-Mol: A Universal 3D Molecular Representation Learning Framework
GROVER (large)
81.0
Self-Supervised Graph Transformer on Large-Scale Molecular Data
GAL 1.3B
57.6
Galactica: A Large Language Model for Science
GAL 30B
72.7
Galactica: A Large Language Model for Science
D-MPNN
80.9
Analyzing Learned Molecular Representations for Property Prediction
GAL 125M
56.1
Galactica: A Large Language Model for Science
MolXPT
88.4
MolXPT: Wrapping Molecules with Text for Generative Pre-training
-
GAL 120B
61.7
Galactica: A Large Language Model for Science
ChemBFN
73.56
A Bayesian Flow Network Framework for Chemistry Tasks
SPMM
83.0
Bidirectional Generation of Structure and Properties Through a Single Molecular Foundation Model
Deep-CBN
83.6
Integrating convolutional layers and biformer network with forward-forward and backpropagation training
GAL 6.7B
58.4
Galactica: A Large Language Model for Science
N-GramXGB
79.1
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules
PretrainGNN
84.5
Strategies for Pre-training Graph Neural Networks
-
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