Shirui Pan

34

Papers

98

Total Citations

Papers (34)

GOODAT: Towards Test-Time Graph Out-of-Distribution Detection

A Label-free Heterophily-guided Approach for Unsupervised Graph Fraud Detection

Graph Sparsification via Mixture of Graphs

Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark

Online GNN Evaluation Under Test-time Graph Distribution Shifts

NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning

BiMark: Unbiased Multilayer Watermarking for Large Language Models

Open-Set Cross-Network Node Classification via Unknown-Excluded Adversarial Graph Domain Alignment

N2GON: Neural Networks for Graph-of-Net with Position Awareness

Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness

Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs

Overcoming Multi-Model Forgetting in One-Shot NAS With Diversity Maximization

Cross-Modal Clinical Graph Transformer for Ophthalmic Report Generation

BaLeNAS: Differentiable Architecture Search via the Bayesian Learning Rule

A Probabilistic Graphical Model Based on Neural-Symbolic Reasoning for Visual Relationship Detection

Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification

Domain-Level Disentanglement Framework Based on Information Enhancement for Cross-Domain Cold-Start Recommendation

Adversarial Contrastive Graph Masked AutoEncoder Against Graph Structure and Feature Dual Attacks

Robust Graph Based Social Recommendation Through Contrastive Multi-View Learning

TGLsta: Low-resource Textual Graph Learning with Semantic and Topological Awareness via LLMs

Augmented Commonsense Knowledge for Remote Object Grounding

ROG\_PL: Robust Open-Set Graph Learning via Region-Based Prototype Learning

Towards Model Extraction Attacks in GAN-Based Image Translation via Domain Shift Mitigation

Position: What Can Large Language Models Tell Us about Time Series Analysis

Graph Geometry Interaction Learning

Differentiable Neural Architecture Search in Equivalent Space with Exploration Enhancement

Graph Stochastic Neural Networks for Semi-supervised Learning

Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels

Pseudo-Riemannian Graph Convolutional Networks

Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination

Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs

Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data

Towards Self-Interpretable Graph-Level Anomaly Detection

GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels