paper-with-me

Graph Regression 벤치마크

Graph Regression on Peptides-struct

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MAE 낮을수록 좋음

0.2393 0.2681 0.297 0.3259 0.3547 2020-07 2026-11 GCNII — 0.3471 (2020-07-04) GPS — 0.25 (2022-05-25) Transformer+LapPE — 0.2529 (2022-06-16) SAN+RWSE — 0.2545 (2022-06-16) SAN+LapPE — 0.2683 (2022-06-16) GatedGCN+RWSE — 0.3357 (2022-06-16) GatedGCN — 0.342 (2022-06-16) GCN — 0.3496 (2022-06-16) GINE — 0.3547 (2022-06-16) TokenGT — 0.2489 (2022-07-06) Graph ViT — 0.2449 (2022-12-27) GraphMLPMixer — 0.2475 (2022-12-27) GCN+virtual node — 0.2488 (2023-01-27) MGT+WavePE — 0.2453 (2023-02-17) Graph Diffuser — 0.2461 (2023-03-01) Exphormer — 0.2481 (2023-03-10) DRew-GCN+LapPE — 0.2536 (2023-05-13) GRIT — 0.246 (2023-05-27) ViT-PS — 0.2559 (2023-06-05) CIN++-500k — 0.2523 (2023-06-06) PathNN — 0.2545 (2023-06-09) NPQ+GATv2 — 0.2589 (2023-07-18) GCN-tuned — 0.246 (2023-09-01) GINE-tuned — 0.2473 (2023-09-01) GatedGCN-tuned — 0.2477 (2023-09-01) GPS-tuned — 0.2509 (2023-09-01) EIGENFORMER — 0.2599 (2024-01-31) TIGT — 0.2485 (2024-02-03) ESA + RWSE (Edge set attention, Random Walk Structural Encoding, tuned) — 0.2393 (2024-02-16) ESA (Edge set attention, no positional encodings, not tuned) — 0.2453 (2024-02-16) CKGCN — 0.2477 (2024-04-21) NeuralWalker — 0.2463 (2024-06-05) GCN + PANDA — 0.3272 (2024-06-06) GatedGCN-HSG — 0.2421 (2024-06-22) BoP — 0.25 (2024-11-17) ECFP + LightGBM — 0.2432 (2025-01-29) TT + LightGBM — 0.2438 (2025-01-29) RDKit + LightGBM — 0.2459 (2025-01-29) GCN+ — 0.2421 (2025-02-13) GCNII — 0.3471 (2020-07-04) GPS — 0.25 (2022-05-25) TokenGT — 0.2489 (2022-07-06) Graph ViT — 0.2449 (2022-12-27) ESA + RWSE (Edge set attention, Random Walk Structural Encoding, tuned) — 0.2393 (2024-02-16)
RankModel MAE PaperCodeYear
1 ESA + RWSE (Edge set attention, Random Walk Structural Encoding, tuned) 0.2393±0.0004 An end-to-end attention-based approach for learning on graphs davidbuterez/edge-set-attention 2024
2 GatedGCN-HSG 0.2421±0.0007 Next Level Message-Passing with Hierarchical Support Graphs carlosinator/support-graphs 2024
3 GCN+ 0.2421 ± 0.0016 Unlocking the Potential of Classic GNNs for Graph-level Tasks: Simple Architectures Meet Excellence LUOyk1999/GNNPlus 2025
4 ECFP + LightGBM 0.2432 Molecular Fingerprints Are Strong Models for Peptide Function Prediction arch4ngel21/scikit-fingerprints · scikit-fingerprints/scikit-fingerprints · scikit-fingerprints/peptides_molecular_fingerprints_classification · +1 2025
5 TT + LightGBM 0.2438 Molecular Fingerprints Are Strong Models for Peptide Function Prediction arch4ngel21/scikit-fingerprints · scikit-fingerprints/scikit-fingerprints · scikit-fingerprints/peptides_molecular_fingerprints_classification · +1 2025
6 Graph ViT 0.2449±0.0016 A Generalization of ViT/MLP-Mixer to Graphs XiaoxinHe/Graph-ViT-MLPMixer · asarigun/GraphMixerNetworks · 2023-MindSpore-1/ms-code-20 2022
7 MGT+WavePE 0.2453±0.0025 Multiresolution Graph Transformers and Wavelet Positional Encoding for Learning Hierarchical Structures vijaydwivedi75/lrgb · hysonlab/multires-graph-transformer 2023
8 ESA (Edge set attention, no positional encodings, not tuned) 0.2453±0.0003 An end-to-end attention-based approach for learning on graphs davidbuterez/edge-set-attention 2024
9 RDKit + LightGBM 0.2459 Molecular Fingerprints Are Strong Models for Peptide Function Prediction arch4ngel21/scikit-fingerprints · scikit-fingerprints/scikit-fingerprints · scikit-fingerprints/peptides_molecular_fingerprints_classification · +1 2025
10 GRIT 0.2460±0.0012 Graph Inductive Biases in Transformers without Message Passing liamma/grit · linusbao/MoSE 2023
11 GCN-tuned 0.2460±0.0007 Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark toenshoff/lrgb · Fedzbar/laser-release 2023
12 Graph Diffuser 0.2461±0.0010 Diffusing Graph Attention 2023
13 NeuralWalker 0.2463 ± 0.0005 Learning Long Range Dependencies on Graphs via Random Walks borgwardtlab/neuralwalker 2024
14 GINE-tuned 0.2473±0.0017 Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark toenshoff/lrgb · Fedzbar/laser-release 2023
15 GraphMLPMixer 0.2475±0.0015 A Generalization of ViT/MLP-Mixer to Graphs XiaoxinHe/Graph-ViT-MLPMixer · asarigun/GraphMixerNetworks · 2023-MindSpore-1/ms-code-20 2022
16 GatedGCN-tuned 0.2477±0.0009 Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark toenshoff/lrgb · Fedzbar/laser-release 2023
17 CKGCN 0.2477 CKGConv: General Graph Convolution with Continuous Kernels networkslab/ckgconv 2024
18 Exphormer 0.2481±0.0007 Exphormer: Sparse Transformers for Graphs hamed1375/exphormer 2023
19 TIGT 0.2485 Topology-Informed Graph Transformer leemingo/tigt · leemingo/cy2mixer 2024
20 GCN+virtual node 0.2488±0.0021 On the Connection Between MPNN and Graph Transformer chen-cai-osu/mpnn-gt-connection 2023
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