Imagen de Portada

Self-supervised Adversarial Purification for Graph Neural Networks

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Lee, Woohyun, Park, Hogun
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

JUDO: A Juxtaposed Domain-Oriented Multimodal Reasoner for Industrial Anomaly QA
por: Kang, Hyunju, et al.
Publicado: (2026)

Balancing Graph Embedding Smoothness in Self-Supervised Learning via Information-Theoretic Decomposition
por: Jung, Heesoo, et al.
Publicado: (2025)

CIMAGE: Exploiting the Conditional Independence in Masked Graph Auto-encoders
por: Park, Jongwon, et al.
Publicado: (2025)

Enhancing Knowledge Tracing with Concept Map and Response Disentanglement
por: Park, Soonwook, et al.
Publicado: (2024)

Curriculum Guided Personalized Subgraph Federated Learning
por: Kang, Minku, et al.
Publicado: (2025)

Hidden costs for inference with deep network on embedded system devices
por: Lee, Chankyu, et al.
Publicado: (2026)

TiGer: Self-Supervised Purification for Time-evolving Graphs
por: Jo, Hyeonsoo, et al.
Publicado: (2025)

Modality-Augmented Fine-Tuning of Foundation Robot Policies for Cross-Embodiment Manipulation on GR1 and G1
por: Park, Junsung, et al.
Publicado: (2025)

UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models
por: Kang, Hyunju, et al.
Publicado: (2026)

Federated Recommender System with Data Valuation for E-commerce Platform
por: Park, Jongwon, et al.
Publicado: (2025)

Applying Self-supervised Learning to Network Intrusion Detection for Network Flows with Graph Neural Network
por: Xu, Renjie, et al.
Publicado: (2024)

Temporal Graph Learning Recurrent Neural Network for Traffic Forecasting
por: Lee, Sanghyun, et al.
Publicado: (2024)

Low-pass Personalized Subgraph Federated Recommendation
por: Sim, Wooseok, et al.
Publicado: (2026)

Large Language Models Are Better Logical Fallacy Reasoners with Counterargument, Explanation, and Goal-Aware Prompt Formulation
por: Jeong, Jiwon, et al.
Publicado: (2025)

HGOT: Self-supervised Heterogeneous Graph Neural Network with Optimal Transport
por: Liu, Yanbei, et al.
Publicado: (2025)

Adversarial Attacks on Fairness of Graph Neural Networks
por: Zhang, Binchi, et al.
Publicado: (2023)

Unsupervised Graph Neural Architecture Search with Disentangled Self-supervision
por: Zhang, Zeyang, et al.
Publicado: (2024)

Graph Neural Diffusion Networks for Semi-supervised Learning
por: Ye, Wei, et al.
Publicado: (2022)

Self-Explainable Temporal Graph Networks based on Graph Information Bottleneck
por: Seo, Sangwoo, et al.
Publicado: (2024)

Self-supervised Subgraph Neural Network With Deep Reinforcement Walk Exploration
por: Huang, Jianming, et al.
Publicado: (2025)

On the Adversarial Robustness of Graph Neural Networks with Graph Reduction
por: Wu, Kerui, et al.
Publicado: (2024)

Adversarial Curriculum Graph-Free Knowledge Distillation for Graph Neural Networks
por: Jia, Yuang, et al.
Publicado: (2025)

Prefixing Attention Sinks can Mitigate Activation Outliers for Large Language Model Quantization
por: Son, Seungwoo, et al.
Publicado: (2024)

Model-Free Adversarial Purification via Coarse-To-Fine Tensor Network Representation
por: Lin, Guang, et al.
Publicado: (2025)

Unifying Adversarial Perturbation for Graph Neural Networks
por: Yang, Jinluan, et al.
Publicado: (2025)

Semantic Graph Neural Network with Multi-measure Learning for Semi-supervised Classification
por: Lin, Junchao, et al.
Publicado: (2022)

Adversarial Training for Graph Neural Networks via Graph Subspace Energy Optimization
por: Liu, Ganlin, et al.
Publicado: (2024)

Graph Positional Autoencoders as Self-supervised Learners
por: Liu, Yang, et al.
Publicado: (2025)

Adversarial Attacks on Locally Private Graph Neural Networks
por: Varun, Matta, et al.
Publicado: (2026)

Online Adversarial Knowledge Distillation for Graph Neural Networks
por: Wang, Can, et al.
Publicado: (2021)

Adversarial Graph Neural Network Benchmarks: Towards Practical and Fair Evaluation
por: Ngo, Tran Gia Bao, et al.
Publicado: (2026)

PAC-Bayesian Adversarially Robust Generalization Bounds for Graph Neural Network
por: Sun, Tan, et al.
Publicado: (2024)

AHSG: Adversarial Attack on High-level Semantics in Graph Neural Networks
por: Yuan, Kai, et al.
Publicado: (2024)

Taming Gradient Oversmoothing and Expansion in Graph Neural Networks
por: Park, MoonJeong, et al.
Publicado: (2024)

Adversarial Attacks on Graph Neural Networks via Meta Learning
por: Zügner, Daniel, et al.
Publicado: (2019)

MADCluster: Model-agnostic Anomaly Detection with Self-supervised Clustering Network
por: Lee, Sangyong, et al.
Publicado: (2025)

Adversarial Graph Fusion for Incomplete Multi-view Semi-supervised Learning with Tensorial Imputation
por: Jiang, Zhangqi, et al.
Publicado: (2025)

Instant Adversarial Purification with Adversarial Consistency Distillation
por: Lei, Chun Tong, et al.
Publicado: (2024)

On the Relationship Between Adversarial Robustness and Decision Region in Deep Neural Networks
por: Park, Seongjin, et al.
Publicado: (2022)

AudioGenX: Explainability on Text-to-Audio Generative Models
por: Kang, Hyunju, et al.
Publicado: (2025)