Graph Regression on Peptides-struct

Metric: MAE (lower is better)

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#	Model↕	MAE▲	Extra Data	Paper	Date↕	Code
1	ECFP + LightGBM	0.2432	No	Molecular Fingerprints Are Strong Models for Pep...	2025-01-29	Code
2	TT + LightGBM	0.2438	No	Molecular Fingerprints Are Strong Models for Pep...	2025-01-29	Code
3	RDKit + LightGBM	0.2459	No	Molecular Fingerprints Are Strong Models for Pep...	2025-01-29	Code
4	CKGCN	0.2477	No	CKGConv: General Graph Convolution with Continuo...	2024-04-21	Code
5	TIGT	0.2485	No	Topology-Informed Graph Transformer	2024-02-03	Code
6	BoP	0.25	No	From Primes to Paths: Enabling Fast Multi-Relati...	2024-11-17	Code
7	CIN++-500k	0.2523	No	CIN++: Enhancing Topological Message Passing	2023-06-06	Code
8	ViT-PS	0.2559	Yes	Learning Probabilistic Symmetrization for Archit...	2023-06-05	Code
9	EIGENFORMER	0.2599	No	Graph Transformers without Positional Encodings	2024-01-31	-

#1ECFP + LightGBMSOTA
0.2432
MAE· 2025-01-29
Molecular Fingerprints Are Strong Models for Peptide Function Prediction Code
#2TT + LightGBMSOTA
0.2438
MAE· 2025-01-29
Molecular Fingerprints Are Strong Models for Peptide Function Prediction Code
#3RDKit + LightGBMSOTA
0.2459
MAE· 2025-01-29
Molecular Fingerprints Are Strong Models for Peptide Function Prediction Code
#4CKGCNSOTA
0.2477
MAE· 2024-04-21
CKGConv: General Graph Convolution with Continuous Kernels Code
#5TIGTSOTA
0.2485
MAE· 2024-02-03
Topology-Informed Graph Transformer Code
#6BoP
0.25
MAE· 2024-11-17
From Primes to Paths: Enabling Fast Multi-Relational Graph Analysis Code
#7CIN++-500kSOTA
0.2523
MAE· 2023-06-06
CIN++: Enhancing Topological Message Passing Code
#8ViT-PSSOTA
0.2559
MAE· Extra Data· 2023-06-05
Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance Code
#9EIGENFORMER
0.2599
MAE· 2024-01-31
Graph Transformers without Positional Encodings