| An end-to-end attention-based approach for learning on graphs | ✓ Link | 0.485±0.009 | 0.944±0.002 | ESA (Edge set attention, no positional encodings) | 2024-02-16 |
| Principal Neighbourhood Aggregation for Graph Nets | ✓ Link | 0.493±0.026 | 0.942±0.006 | PNA | 2020-04-12 |
| How Powerful are Graph Neural Networks? | ✓ Link | 0.509±0.044 | 0.938±0.011 | GIN | 2018-10-01 |
| Semi-Supervised Classification with Graph Convolutional Networks | ✓ Link | 0.520±0.024 | 0.936±0.006 | GCN | 2016-09-09 |
| DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks | ✓ Link | 0.520±0.048 | 0.935±0.012 | DropGIN | 2021-11-11 |
| Graph Attention Networks | ✓ Link | 0.540±0.027 | 0.930±0.007 | GAT | 2017-10-30 |
| How Attentive are Graph Attention Networks? | ✓ Link | 0.549±0.020 | 0.928±0.005 | GATv2 | 2021-05-30 |
| MoleculeNet: A Benchmark for Molecular Machine Learning | ✓ Link | 0.58 | | MPNN | 2017-03-02 |
| Recipe for a General, Powerful, Scalable Graph Transformer | ✓ Link | 0.613±0.010 | 0.911±0.003 | GraphGPS | 2022-05-25 |
| Do Transformers Really Perform Bad for Graph Representation? | ✓ Link | 0.618±0.068 | 0.908±0.021 | Graphormer | 2021-06-09 |
| Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning | ✓ Link | 0.623 | | SMA | 2024-02-22 |
| Pure Transformers are Powerful Graph Learners | ✓ Link | 0.667±0.103 | 0.892±0.036 | TokenGT | 2022-07-06 |
| Uni-Mol: A Universal 3D Molecular Representation Learning Framework | ✓ Link | 0.788 | | Uni-Mol | 2022-09-08 |
| ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction | | 0.798 | | ChemRL-GEM | 2021-06-11 |
| Bidirectional Generation of Structure and Properties Through a Single Molecular Foundation Model | ✓ Link | 0.810 | | SPMM | 2022-11-19 |
| Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck | ✓ Link | 0.816±0.019 | | S-CGIB | 2025-02-20 |
| A Bayesian Flow Network Framework for Chemistry Tasks | ✓ Link | 0.884 | | ChemBFN | 2024-07-28 |
| ChemBERTa-2: Towards Chemical Foundation Models | ✓ Link | 0.889 | | ChemBERTa-2 (MTR-77M) | 2022-09-05 |
| MoleculeNet: A Benchmark for Molecular Machine Learning | ✓ Link | 0.99 | | XGBoost | 2017-03-02 |
| Analyzing Learned Molecular Representations for Property Prediction | ✓ Link | 1.050 | | D-MPNN | 2019-04-02 |