SOTAVerified

Graph Property Prediction

Papers

Showing 1–10 of 56 papers

TitleStatusHype
Graph Positional Autoencoders as Self-supervised Learners—0
Message-Passing State-Space Models: Improving Graph Learning with Modern Sequence Modeling—0
GotenNet: Rethinking Efficient 3D Equivariant Graph Neural NetworksCode2
Unlocking the Potential of Classic GNNs for Graph-level Tasks: Simple Architectures Meet ExcellenceCode2
Graph Generative Pre-trained Transformer—0
Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph LearningCode0
Data-Driven Self-Supervised Graph Representation LearningCode0
Next Level Message-Passing with Hierarchical Support GraphsCode0
Towards Neural Scaling Laws for Foundation Models on Temporal GraphsCode1
Learning Long Range Dependencies on Graphs via Random WalksCode1
Show:102550
← PrevPage 1 of 6Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Graphormer (pre-trained on PCQM4M)Number of params47,183,040—Unverified
2GraphormerNumber of params47,183,040—Unverified
3Graphormer + FPsNumber of params47,085,378—Unverified
4PAS+FPsNumber of params26,706,953—Unverified
5HyperFusionNumber of params5,908,027—Unverified
6P-WLNumber of params4,600,000—Unverified
7DeepAUCNumber of params3,444,509—Unverified
8GSNNumber of params3,338,701—Unverified
9GIN+virtual nodeNumber of params3,336,306—Unverified
10GIN+virtual node+FLAGNumber of params3,336,306—Unverified