An end-to-end attention-based approach for learning on graphs | ✓ Link | 0.7479 | ESA + RWSE (Edge set attention, Random Walk Structural Encoding, + validation set) | 2024-02-16 |
Molecular Fingerprints Are Strong Models for Peptide Function Prediction | ✓ Link | 0.7460 | ECFP + LightGBM | 2025-01-29 |
An end-to-end attention-based approach for learning on graphs | ✓ Link | 0.7357±0.0036 | ESA + RWSE (Edge set attention, Random Walk Structural Encoding, tuned) | 2024-02-16 |
Molecular Fingerprints Are Strong Models for Peptide Function Prediction | ✓ Link | 0.7318 | TT + LightGBM | 2025-01-29 |
Spatio-Spectral Graph Neural Networks | ✓ Link | 0.7311±0.0066 | S²GCN | 2024-05-29 |
Molecular Fingerprints Are Strong Models for Peptide Function Prediction | ✓ Link | 0.7311 | RDKit + LightGBM | 2025-01-29 |
Unlocking the Potential of Classic GNNs for Graph-level Tasks: Simple Architectures Meet Excellence | ✓ Link | 0.7261 ± 0.0067 | GCN+ | 2025-02-13 |
Enhancing Graph Transformers with Hierarchical Distance Structural Encoding | ✓ Link | 0.7156±0.0058 | GraphGPS + HDSE | 2023-08-22 |
DRew: Dynamically Rewired Message Passing with Delay | ✓ Link | 0.7150±0.0044 | DRew-GCN+LapPE | 2023-05-13 |
Recurrent Distance Filtering for Graph Representation Learning | ✓ Link | 0.7133±0.0011 | GRED+LapPE | 2023-12-03 |
Learning Long Range Dependencies on Graphs via Random Walks | ✓ Link | 0.7096 ± 0.0078 | NeuralWalker | 2024-06-05 |
Recurrent Distance Filtering for Graph Representation Learning | ✓ Link | 0.7085±0.0027 | GRED | 2023-12-03 |
An end-to-end attention-based approach for learning on graphs | ✓ Link | 0.7071±0.0015 | ESA (Edge set attention, no positional encodings, tuned) | 2024-02-16 |
Graph Inductive Biases in Transformers without Message Passing | ✓ Link | 0.6988±0.0082 | GRIT | 2023-05-27 |
CKGConv: General Graph Convolution with Continuous Kernels | ✓ Link | 0.6952 | CKGCN | 2024-04-21 |
A Generalization of ViT/MLP-Mixer to Graphs | ✓ Link | 0.6942±0.0075 | Graph ViT | 2022-12-27 |
A Generalization of ViT/MLP-Mixer to Graphs | ✓ Link | 0.6921±0.0054 | GraphMLPMixer | 2022-12-27 |
Next Level Message-Passing with Hierarchical Support Graphs | ✓ Link | 0.6866±0.0038 | GatedGCN-HSG | 2024-06-22 |
An end-to-end attention-based approach for learning on graphs | ✓ Link | 0.6863±0.0044 | ESA (Edge set attention, no positional encodings, not tuned) | 2024-02-16 |
Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark | ✓ Link | 0.6860±0.0050 | GCN-tuned | 2023-09-01 |
Multiresolution Graph Transformers and Wavelet Positional Encoding for Learning Hierarchical Structures | ✓ Link | 0.6817±0.0064 | MGT+WavePE | 2023-02-17 |
Path Neural Networks: Expressive and Accurate Graph Neural Networks | ✓ Link | 0.6816±0.0026 | PathNN | 2023-06-09 |
Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark | ✓ Link | 0.6765±0.0047 | GatedGCN-tuned | 2023-09-01 |
On the Connection Between MPNN and Graph Transformer | ✓ Link | 0.6685±0.0062 | GatedGCN+RWSE+virtual node | 2023-01-27 |
Topology-Informed Graph Transformer | ✓ Link | 0.6679 | TIGT | 2024-02-03 |
Diffusing Graph Attention | | 0.6651±0.0010 | Graph Diffuser | 2023-03-01 |
Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark | ✓ Link | 0.6621±0.0067 | GINE-tuned | 2023-09-01 |
Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance | ✓ Link | 0.6575 | ViT-PS | 2023-06-05 |
CIN++: Enhancing Topological Message Passing | ✓ Link | 0.6569±0.0117 | CIN++-500k | 2023-06-06 |
Recipe for a General, Powerful, Scalable Graph Transformer | ✓ Link | 0.6535±0.0041 | GPS | 2022-05-25 |
Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark | ✓ Link | 0.6534±0.0091 | GPS-tuned | 2023-09-01 |
Exphormer: Sparse Transformers for Graphs | ✓ Link | 0.6527±0.0043 | Exphormer | 2023-03-10 |
Molecular Topological Profile (MOLTOP) - Simple and Strong Baseline for Molecular Graph Classification | ✓ Link | 0.6459 ± 0.0005 | MOLTOP | 2024-10-17 |
Long Range Graph Benchmark | ✓ Link | 0.6439±0.0075 | SAN+RWSE | 2022-06-16 |
Graph Transformers without Positional Encodings | | 0.6414 | EIGENFORMER | 2024-01-31 |
Long Range Graph Benchmark | ✓ Link | 0.6384±0.0121 | SAN+LapPE | 2022-06-16 |
Long Range Graph Benchmark | ✓ Link | 0.6326±0.0126 | Transformer+LapPE | 2022-06-16 |
Long Range Graph Benchmark | ✓ Link | 0.6069±0.0035 | GatedGCN+RWSE | 2022-06-16 |
How Powerful are Graph Neural Networks? | ✓ Link | 0.6043±0.0216 | GIN | 2018-10-01 |
PANDA: Expanded Width-Aware Message Passing Beyond Rewiring | ✓ Link | 0.6028±0.0031 | GCN + PANDA | 2024-06-06 |
Long Range Graph Benchmark | ✓ Link | 0.5930±0.0023 | GCN | 2022-06-16 |
Long Range Graph Benchmark | ✓ Link | 0.5864±0.0077 | GatedGCN | 2022-06-16 |
Simple and Deep Graph Convolutional Networks | ✓ Link | 0.5543±0.0078 | GCNII | 2020-07-04 |
Long Range Graph Benchmark | ✓ Link | 0.5498±0.0079 | GINE | 2022-06-16 |