SOTAVerified

Graph Regression

The regression task is similar to graph classification but using different loss function and performance metric.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–10 of 145 papers

TitleStatusHype
Graph Neural Networks for Jamming Source LocalizationCode0
A Benchmark Dataset for Graph Regression with Homogeneous and Multi-Relational Variants—0
Improving the Effective Receptive Field of Message-Passing Neural NetworksCode1
GotenNet: Rethinking Efficient 3D Equivariant Graph Neural NetworksCode2
Power Spectrum Signatures of Graphs—0
Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information BottleneckCode1
Unlocking the Potential of Classic GNNs for Graph-level Tasks: Simple Architectures Meet ExcellenceCode2
Learning Efficient Positional Encodings with Graph Neural NetworksCode1
Beyond Message Passing: Neural Graph Pattern MachineCode1
Molecular Fingerprints Are Strong Models for Peptide Function PredictionCode3
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All datasetsZINC-500kZINCPCQM4Mv2-LSCLipophilicityPCQM4M-LSCPeptides-structZINC 100kTox21ZINC-fullESOLQM9QM9: del e

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Graph-JEPAMAE0.43—Unverified
2FactorGCNMAE0.37—Unverified
3ChebNetMAE0.36—Unverified
4BoPMAE0.3—Unverified
5MMAMAE0.16—Unverified
6PNAMAE0.14—Unverified
7CRaWlMAE0.1—Unverified
8PINMAE0.1—Unverified
9CIN-smallMAE0.09—Unverified
10CIN++-smallMAE0.09—Unverified