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graph classification

212 papers

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Co-occurring keywords

graph neural network (3945) node classification (480) graph kernel (66) representation learning (6174) graph representation learning (246) graph pooling (38) graph convolution (183) graph representation (359) contrastive learning (3979) kernel methods (1096)

Papers

A Gromov-Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening ICML 2023
Geometric Random Walk Graph Neural Networks via Implicit Layers AISTATS 2023
GSLB: The Graph Structure Learning Benchmark NIPS 2023
Deep Graph Reprogramming CVPR 2023
CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification ICML 2023
All in a Row: Compressed Convolution Networks for Graphs ICML 2023
Graph Alignment Kernels using Weisfeiler and Leman Hierarchies AISTATS 2023
Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks NIPS 2023
Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning NIPS 2023
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks IJCAI 2022
TGNN: A Joint Semi-supervised Framework for Graph-level Classification IJCAI 2022
High-Order Pooling for Graph Neural Networks with Tensor Decomposition NIPS 2022
Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs AAAI 2022
GraphDIVE: Graph Classification by Mixture of Diverse Experts IJCAI 2022
GraphQNTK: Quantum Neural Tangent Kernel for Graph Data NIPS 2022
Structural Landmarking and Interaction Modelling: A “SLIM” Network for Graph Classification AAAI 2022
Graph Filtration Kernels AAAI 2022
Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation AAAI 2022
KerGNNs: Interpretable Graph Neural Networks with Graph Kernels AAAI 2022
Filtration-Enhanced Graph Transformation IJCAI 2022
Graph Scattering beyond Wavelet Shackles NIPS 2022
Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited NIPS 2022
Rethinking the Setting of Semi-supervised Learning on Graphs IJCAI 2022
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs NIPS 2022
SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks NIPS 2022