Co-occurring keywords · papers mentioning both
Papers
SkipPool: Improved Sparse Hierarchical Graph Pooling with Differentiable Exploration
AAAI 2025
Structural Entropy Guided Unsupervised Graph Out-Of-Distribution Detection
AAAI 2025
Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classifications
AAAI 2025
When Hypergraph Meets Heterophily: New Benchmark Datasets and Baseline
AAAI 2025
BLIS-Net: Classifying and Analyzing Signals on Graphs
AISTATS 2024
Deep Hierarchical Graph Alignment Kernels
IJCAI 2024
Differentiable Euler Characteristic Transforms for Shape Classification
ICLR 2024
Efficient Algorithms for Learning Monophonic Halfspaces in Graphs
COLT 2024
Enhancing Graph Transformers with Hierarchical Distance Structural Encoding
NeurIPS 2024
EPIC: Graph Augmentation with Edit Path Interpolation via Learnable Cost
IJCAI 2024
Exploring Consistency in Graph Representations: from Graph Kernels to Graph Neural Networks
NeurIPS 2024
Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers
NeurIPS 2024
GC-Bench: An Open and Unified Benchmark for Graph Condensation
NeurIPS 2024
GCVR: Reconstruction from Cross-View Enable Sufficient and Robust Graph Contrastive Learning
UAI 2024
GNNBoundary: Towards Explaining Graph Neural Networks through the Lens of Decision Boundaries
ICLR 2024
GNNCert: Deterministic Certification of Graph Neural Networks against Adversarial Perturbations
ICLR 2024
Graph Classification via Reference Distribution Learning: Theory and Practice
NeurIPS 2024
Graph Parsing Networks
ICLR 2024
HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning
NeurIPS 2024
Kernel Readout for Graph Neural Networks
IJCAI 2024
Label Attentive Distillation for GNN-Based Graph Classification
AAAI 2024
Mirage: Model-agnostic Graph Distillation for Graph Classification
ICLR 2024
MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy
ICLR 2024
Non-convolutional graph neural networks.
NeurIPS 2024
One For All: Towards Training One Graph Model For All Classification Tasks
ICLR 2024