OpenCodePapers

graph-regression-on-zinc

Graph Regression
Dataset Link
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PaperCodeMAEModelNameReleaseDate
An end-to-end attention-based approach for learning on graphs✓ Link0.051ESA + rings + NodeRWSE + EdgeRWSE2024-02-16
Self-Attention in Colors: Another Take on Encoding Graph Structure in Transformers✓ Link0.056CSA2023-04-21
Topology-Informed Graph Transformer✓ Link0.057TIGT2024-02-03
Graph Inductive Biases in Transformers without Message Passing✓ Link0.059GRIT2023-05-27
Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman✓ Link0.059N2-GNN2023-06-05
CKGConv: General Graph Convolution with Continuous Kernels✓ Link0.059CKGCN2024-04-21
Learning Long Range Dependencies on Graphs via Random Walks✓ Link0.065 ± 0.001NeuralWalker2024-06-05
Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering✓ Link0.066 ± 0.002PDF2023-05-10
Recipe for a General, Powerful, Scalable Graph Transformer✓ Link0.070 ± 0.002GPS2022-05-25
Recipe for a General, Powerful, Scalable Graph Transformer✓ Link0.070 ± 0.004GINE2022-05-25
Substructure Aware Graph Neural Networks✓ Link0.072±0.002SAGNN2023-06-26
CIN++: Enhancing Topological Message Passing✓ Link0.074CIN++2023-06-06
A Generalization of ViT/MLP-Mixer to Graphs✓ Link0.075 ± 0.001GraphMLPMixer2022-12-27
CIN++: Enhancing Topological Message Passing✓ Link0.077CIN++-500k2023-06-06
Graph Transformers without Positional Encodings0.077EIGENFORMER2024-01-31
Weisfeiler and Lehman Go Cellular: CW Networks✓ Link0.079CIN2021-06-23
Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing✓ Link0.088CRaWl+VN2021-02-17
CIN++: Enhancing Topological Message Passing✓ Link0.091CIN++-small2023-06-06
Weisfeiler and Lehman Go Cellular: CW Networks✓ Link0.094CIN-small2021-06-23
Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes0.096PIN2023-08-13
Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing✓ Link0.101CRaWl2021-02-17
Principal Neighbourhood Aggregation for Graph Nets✓ Link0.142PNA2020-04-12
Multi-Mask Aggregators for Graph Neural Networks✓ Link0.156MMA2022-11-24
From Primes to Paths: Enabling Fast Multi-Relational Graph Analysis✓ Link0.297BoP2024-11-17
An Experimental Study of the Transferability of Spectral Graph Networks✓ Link0.360ChebNet2020-12-18
Factorizable Graph Convolutional Networks✓ Link0.366FactorGCN2020-10-12
Graph-level Representation Learning with Joint-Embedding Predictive Architectures✓ Link0.434Graph-JEPA2023-09-27