:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Llorente, Oscar, Boal, Jaime, Sánchez-Úbeda, Eugenio F., Diaz-Cano, Antonio, Familiar, Miguel
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2601.04807
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Evaluating Neighbor Explainability for Graph Neural Networks
by: Llorente, Oscar, et al.
Published: (2023)

One Node Per User: Node-Level Federated Learning for Graph Neural Networks
by: Gao, Zhidong, et al.
Published: (2024)

Explaining Graph Neural Networks for Node Similarity on Graphs
by: Daza, Daniel, et al.
Published: (2024)

Graph Unlearning: Efficient Node Removal in Graph Neural Networks
by: Guan, Faqian, et al.
Published: (2025)

Trainable and Explainable Simplicial Map Neural Networks
by: Paluzo-Hidalgo, Eduardo, et al.
Published: (2023)

On the Utilization of Unique Node Identifiers in Graph Neural Networks
by: Bechler-Speicher, Maya, et al.
Published: (2024)

TinyGraph: Joint Feature and Node Condensation for Graph Neural Networks
by: Liu, Yezi, et al.
Published: (2024)

Explainable Graph Neural Networks Under Fire
by: Li, Zhong, et al.
Published: (2024)

A Transformer approach for Electricity Price Forecasting
by: Llorente, Oscar, et al.
Published: (2024)

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning
by: Zhang, Yuelin, et al.
Published: (2025)

ENADPool: The Edge-Node Attention-based Differentiable Pooling for Graph Neural Networks
by: Zhao, Zhehan, et al.
Published: (2024)

Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks
by: Abbahaddou, Yassine, et al.
Published: (2024)

Enhancing Fairness in Autoencoders for Node-Level Graph Anomaly Detection
by: Wang, Shouju, et al.
Published: (2025)

GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks
by: Amara, Kenza, et al.
Published: (2022)

Explainable Global Wildfire Prediction Models using Graph Neural Networks
by: Chen, Dayou, et al.
Published: (2024)

SES: Bridging the Gap Between Explainability and Prediction of Graph Neural Networks
by: Huang, Zhenhua, et al.
Published: (2024)

RoCP-GNN: Robust Conformal Prediction for Graph Neural Networks in Node-Classification
by: Akansha, S.
Published: (2024)

ASPECT: Node-Level Adaptive Spectral Fusion for Graph Contrastive Learning
by: Li, Zhuolong, et al.
Published: (2026)

Disentangled and Self-Explainable Node Representation Learning
by: Piaggesi, Simone, et al.
Published: (2024)

FlowX: Towards Explainable Graph Neural Networks via Message Flows
by: Gui, Shurui, et al.
Published: (2022)

A Diffusion-Contrastive Graph Neural Network with Virtual Nodes for Wind Nowcasting in Unobserved Regions
by: Shi, Jie, et al.
Published: (2026)

Deep Graph Neural Networks via Posteriori-Sampling-based Node-Adaptive Residual Module
by: Zhou, Jingbo, et al.
Published: (2023)

Beyond Fixed Depth: Adaptive Graph Neural Networks for Node Classification Under Varying Homophily
by: Hevapathige, Asela, et al.
Published: (2025)

Graph Similarity Computation via Interpretable Neural Node Alignment
by: Wang, Jingjing, et al.
Published: (2024)

Node Level Graph Autoencoder: Unified Pretraining for Textual Graph Learning
by: Hu, Wenbin, et al.
Published: (2024)

From Text to Graph: Leveraging Graph Neural Networks for Enhanced Explainability in NLP
by: Yáñez-Romero, Fabio, et al.
Published: (2025)

GNN-XAR: A Graph Neural Network for Explainable Activity Recognition in Smart Homes
by: Fiori, Michele, et al.
Published: (2025)

Graph Neural Network contextual embedding for Deep Learning on Tabular Data
by: Villaizán-Vallelado, Mario, et al.
Published: (2023)

GMLM: Bridging Graph Neural Networks and Language Models for Heterophilic Node Classification
by: Sinha, Aarush
Published: (2025)

Deeply Explainable Artificial Neural Network
by: Zucker, David
Published: (2025)

Graph-Level Label-Only Membership Inference Attack against Graph Neural Networks
by: Dai, Jiazhu, et al.
Published: (2025)

Pure Node Selection for Imbalanced Graph Node Classification
by: Zeng, Fanlong, et al.
Published: (2025)

Energy Consumption in Parallel Neural Network Training
by: Huber, Philipp, et al.
Published: (2025)

Formal Verification of Graph Convolutional Networks with Uncertain Node Features and Uncertain Graph Structure
by: Ladner, Tobias, et al.
Published: (2024)

PIMPC-GNN: Physics-Informed Multi-Phase Consensus Learning for Enhancing Imbalanced Node Classification in Graph Neural Networks
by: Fofanah, Abdul Joseph, et al.
Published: (2026)

Explainable Anomaly Detection for Electric Vehicles Charging Stations
by: Cederle, Matteo, et al.
Published: (2025)

GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
by: Wang, Xiaoqi, et al.
Published: (2022)

Enhancing Explainability of Graph Neural Networks Through Conceptual and Structural Analyses and Their Extensions
by: Bui, Tien Cuong
Published: (2025)

OpenGLT: A Comprehensive Benchmark of Graph Neural Networks for Graph-Level Tasks
by: Li, Haoyang, et al.
Published: (2025)

Compressing Deep Neural Networks Using Explainable AI
by: Soroush, Kimia, et al.
Published: (2025)