Showing 1–20 of 55 results
/ Date/ Name
Nov 13, 2020Learning to Drop: Robust Graph Neural Network via Topological DenoisingNov 9, 2020Attentive Social Recommendation: Towards User And Item DiversitiesOct 12, 2023CLExtract: Recovering Highly Corrupted DVB/GSE Satellite Stream with Contrastive LearningFeb 16, 2024Parametric Augmentation for Time Series Contrastive LearningOct 16, 2024Explanation-Preserving Augmentation for Semi-Supervised Graph Representation LearningJul 4, 2023Random Walk on Multiple NetworksJun 4, 2025SF$^2$Bench: Evaluating Data-Driven Models for Compound Flood Forecasting in South FloridaOct 3, 2024F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AINov 9, 2020Parameterized Explainer for Graph Neural NetworkOct 3, 2023Towards Robust Fidelity for Evaluating Explainability of Graph Neural NetworksDec 9, 2023Factorized Explainer for Graph Neural NetworksMar 26, 2021Unsupervised Document Embedding via Contrastive AugmentationFeb 7, 2024PAC Learnability under Explanation-Preserving Graph PerturbationsFeb 3, 2024Generating In-Distribution Proxy Graphs for Explaining Graph Neural NetworksOct 26, 2022Personalized Federated Learning via Heterogeneous Modular NetworksOct 25, 2023DyExplainer: Explainable Dynamic Graph Neural NetworksOct 16, 2023Shape-aware Graph Spectral LearningJan 31, 2024Rank Supervised Contrastive Learning for Time Series ClassificationApr 15, 2024Polynomial Selection in Spectral Graph Neural Networks: An Error-Sum of Function Slices ApproachJul 15, 2023RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks