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Graph Neural Networks

1127 directly classified papers

Papers per year

Papers

Exposing the Self-Supervised Space-Time Correspondence Learning via Graph Kernels AAAI 2023
Data Imputation with Iterative Graph Reconstruction AAAI 2023
Heterogeneous Graph Learning for Multi-Modal Medical Data Analysis AAAI 2023
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks AAAI 2023
Ewald-based Long-Range Message Passing for Molecular Graphs ICML 2023
Autoregressive Diffusion Model for Graph Generation ICML 2023
GOAT: A Global Transformer on Large-scale Graphs ICML 2023
On the Expressive Power of Geometric Graph Neural Networks ICML 2023
Self-Supervised Graph Learning for Long-Tailed Cognitive Diagnosis AAAI 2023
Leveraging Label Non-Uniformity for Node Classification in Graph Neural Networks ICML 2023
A Generalization of ViT/MLP-Mixer to Graphs ICML 2023
Total Variation Graph Neural Networks ICML 2023
Conformal Prediction Sets for Graph Neural Networks ICML 2023
Neighborhood-Regularized Self-Training for Learning with Few Labels AAAI 2023
TopicFM: Robust and Interpretable Topic-Assisted Feature Matching AAAI 2023
DRew: Dynamically Rewired Message Passing with Delay ICML 2023
GRAFENNE: Learning on Graphs with Heterogeneous and Dynamic Feature Sets ICML 2023
TIDE: Time Derivative Diffusion for Deep Learning on Graphs ICML 2023
Half-Hop: A graph upsampling approach for slowing down message passing ICML 2023
Sentiment Analysis using the Relationship between Users and Products ACL 2023
Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis AAAI 2023
Dual Low-Rank Graph Autoencoder for Semantic and Topological Networks AAAI 2023
Restructuring Graph for Higher Homophily via Adaptive Spectral Clustering AAAI 2023
Exploring Faithful Rationale for Multi-Hop Fact Verification via Salience-Aware Graph Learning AAAI 2023
Topological Pooling on Graphs AAAI 2023