From Binary to Continuous: Stochastic Re-Weighting for Robust Graph Explanation
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Zhuomin, Ni, Jingchao, Salehi, Hojat Allah, Zheng, Xu, Luo, Dongsheng |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Explanation-Preserving Augmentation for Semi-Supervised Graph Representation Learning
by: Chen, Zhuomin, et al.
Published: (2024)
by: Chen, Zhuomin, et al.
Published: (2024)
Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks
by: Chen, Zhuomin, et al.
Published: (2024)
by: Chen, Zhuomin, et al.
Published: (2024)
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks
by: Zheng, Xu, et al.
Published: (2023)
by: Zheng, Xu, et al.
Published: (2023)
RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks
by: Zhang, Jiaxing, et al.
Published: (2023)
by: Zhang, Jiaxing, et al.
Published: (2023)
F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI
by: Zheng, Xu, et al.
Published: (2024)
by: Zheng, Xu, et al.
Published: (2024)
TimeX++: Learning Time-Series Explanations with Information Bottleneck
by: Liu, Zichuan, et al.
Published: (2024)
by: Liu, Zichuan, et al.
Published: (2024)
DRIFT: A Benchmark for Task-Free Continual Graph Learning with Continuous Distribution Shifts
by: Sun, Guiquan, et al.
Published: (2026)
by: Sun, Guiquan, et al.
Published: (2026)
HERO: Heterogeneous Continual Graph Learning via Meta-Knowledge Distillation
by: Sun, Guiquan, et al.
Published: (2025)
by: Sun, Guiquan, et al.
Published: (2025)
PAC Learnability under Explanation-Preserving Graph Perturbations
by: Zheng, Xu, et al.
Published: (2024)
by: Zheng, Xu, et al.
Published: (2024)
CorBin-FL: A Differentially Private Federated Learning Mechanism using Common Randomness
by: Salehi, Hojat Allah, et al.
Published: (2024)
by: Salehi, Hojat Allah, et al.
Published: (2024)
LM$^2$otifs : An Explainable Framework for Machine-Generated Texts Detection
by: Zheng, Xu, et al.
Published: (2025)
by: Zheng, Xu, et al.
Published: (2025)
Is Your Explanation Reliable: Confidence-Aware Explanation on Graph Neural Networks
by: Zhang, Jiaxing, et al.
Published: (2025)
by: Zhang, Jiaxing, et al.
Published: (2025)
Exploring Multi-Modal Data with Tool-Augmented LLM Agents for Precise Causal Discovery
by: Shen, ChengAo, et al.
Published: (2024)
by: Shen, ChengAo, et al.
Published: (2024)
Robust Stochastic Graph Generator for Counterfactual Explanations
by: Prado-Romero, Mario Alfonso, et al.
Published: (2023)
by: Prado-Romero, Mario Alfonso, et al.
Published: (2023)
On Non-Interactive Simulation of Distributed Sources with Finite Alphabets
by: Salehi, Hojat Allah, et al.
Published: (2024)
by: Salehi, Hojat Allah, et al.
Published: (2024)
SF$^2$Bench: Evaluating Data-Driven Models for Compound Flood Forecasting in South Florida
by: Zheng, Xu, et al.
Published: (2025)
by: Zheng, Xu, et al.
Published: (2025)
Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape
by: Chen, Tiejin, et al.
Published: (2024)
by: Chen, Tiejin, et al.
Published: (2024)
Explanation-Guided Adversarial Training for Robust and Interpretable Models
by: Chen, Chao, et al.
Published: (2026)
by: Chen, Chao, et al.
Published: (2026)
BAED: a New Paradigm for Few-shot Graph Learning with Explanation in the Loop
by: Chen, Chao, et al.
Published: (2026)
by: Chen, Chao, et al.
Published: (2026)
SVTime: Small Time Series Forecasting Models Informed by "Physics" of Large Vision Model Forecasters
by: Shen, ChengAo, et al.
Published: (2025)
by: Shen, ChengAo, et al.
Published: (2025)
LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation
by: Zhang, Jiaxing, et al.
Published: (2024)
by: Zhang, Jiaxing, et al.
Published: (2024)
Bipartite Graph Attention-based Clustering for Large-scale scRNA-seq Data
by: Liang, Zhuomin, et al.
Published: (2026)
by: Liang, Zhuomin, et al.
Published: (2026)
MELODY: Robust Semi-Supervised Hybrid Model for Entity-Level Online Anomaly Detection with Multivariate Time Series
by: Ni, Jingchao, et al.
Published: (2024)
by: Ni, Jingchao, et al.
Published: (2024)
Quantum Advantage in Non-Interactive Source Simulation
by: Salehi, Hojat Allah, et al.
Published: (2024)
by: Salehi, Hojat Allah, et al.
Published: (2024)
Factorized Explainer for Graph Neural Networks
by: Huang, Rundong, et al.
Published: (2023)
by: Huang, Rundong, et al.
Published: (2023)
Harnessing Vision Models for Time Series Analysis: A Survey
by: Ni, Jingchao, et al.
Published: (2025)
by: Ni, Jingchao, et al.
Published: (2025)
Shape-aware Graph Spectral Learning
by: Xu, Junjie, et al.
Published: (2023)
by: Xu, Junjie, et al.
Published: (2023)
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling
by: Zhao, Tianxiang, et al.
Published: (2024)
by: Zhao, Tianxiang, et al.
Published: (2024)
LUMOS: Democratizing SciML Workflows with L0-Regularized Learning for Unified Feature and Parameter Adaptation
by: Gao, Shouwei, et al.
Published: (2026)
by: Gao, Shouwei, et al.
Published: (2026)
Scalable Expressiveness through Preprocessed Graph Perturbations
by: Saber, Danial, et al.
Published: (2024)
by: Saber, Danial, et al.
Published: (2024)
Efficient and Robust Continual Graph Learning for Graph Classification in Biology
by: Zhang, Ding, et al.
Published: (2024)
by: Zhang, Ding, et al.
Published: (2024)
Domain-Incremental Continual Learning for Robust and Efficient Keyword Spotting in Resource Constrained Systems
by: Dhungana, Prakash, et al.
Published: (2026)
by: Dhungana, Prakash, et al.
Published: (2026)
Continual Graph Learning: A Survey
by: Yuan, Qiao, et al.
Published: (2023)
by: Yuan, Qiao, et al.
Published: (2023)
Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization
by: Kumar, Ramnath, et al.
Published: (2023)
by: Kumar, Ramnath, et al.
Published: (2023)
Graph Diffusion Counterfactual Explanation
by: Bechtoldt, David, et al.
Published: (2025)
by: Bechtoldt, David, et al.
Published: (2025)
Predicting Fatigue Crack Growth via Path Slicing and Re-Weighting
by: Zhao, Yingjie, et al.
Published: (2023)
by: Zhao, Yingjie, et al.
Published: (2023)
GraphNarrator: Generating Textual Explanations for Graph Neural Networks
by: Pan, Bo, et al.
Published: (2024)
by: Pan, Bo, et al.
Published: (2024)
Provable Robust Saliency-based Explanations
by: Chen, Chao, et al.
Published: (2022)
by: Chen, Chao, et al.
Published: (2022)
UFO: A Unified Flow-Oriented Framework for Robust Continual Graph Learning
by: Zhang, Danhui, et al.
Published: (2026)
by: Zhang, Danhui, et al.
Published: (2026)
Elastic Weight Consolidation for Knowledge Graph Continual Learning: An Empirical Evaluation
by: Jhajj, Gaganpreet, et al.
Published: (2025)
by: Jhajj, Gaganpreet, et al.
Published: (2025)
Similar Items
-
Explanation-Preserving Augmentation for Semi-Supervised Graph Representation Learning
by: Chen, Zhuomin, et al.
Published: (2024) -
Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks
by: Chen, Zhuomin, et al.
Published: (2024) -
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks
by: Zheng, Xu, et al.
Published: (2023) -
RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks
by: Zhang, Jiaxing, et al.
Published: (2023) -
F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI
by: Zheng, Xu, et al.
Published: (2024)