:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Hasegawa, Tai, Yun, Sukwon, Liu, Xin, Phua, Yin Jun, Murata, Tsuyoshi
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2404.09207
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Future-Proofing Class-Incremental Learning
by: Jodelet, Quentin, et al.
Published: (2024)

Oldie but Goodie: Re-illuminating Label Propagation on Graphs with Partially Observed Features
by: Yun, Sukwon, et al.
Published: (2025)

Training Robust Graph Neural Networks by Modeling Noise Dependencies
by: In, Yeonjun, et al.
Published: (2025)

Variable Assignment Invariant Neural Networks for Learning Logic Programs
by: Phua, Yin Jun, et al.
Published: (2024)

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

Adaptive Node Feature Selection For Graph Neural Networks
by: Navarro, Madeline, et al.
Published: (2025)

Node-wise Filtering in Graph Neural Networks: A Mixture of Experts Approach
by: Han, Haoyu, et al.
Published: (2024)

BRAVA-GNN: Betweenness Ranking Approximation Via Degree MAss Inspired Graph Neural Network
by: Dachille, Justin, et al.
Published: (2026)

Variational Adaptive Noise and Dropout towards Stable Recurrent Neural Networks
by: Kobayashi, Taisuke, et al.
Published: (2025)

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

I2MoE: Interpretable Multimodal Interaction-aware Mixture-of-Experts
by: Xin, Jiayi, et al.
Published: (2025)

Flex-MoE: Modeling Arbitrary Modality Combination via the Flexible Mixture-of-Experts
by: Yun, Sukwon, et al.
Published: (2024)

Self-Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks
by: Wei, Jianjun, et al.
Published: (2024)

Graph Attention Specialized Expert Fusion Model for Node Classification: Based on Cora and Pubmed Datasets
by: Ma, Zihang, et al.
Published: (2025)

Edge Conditional Node Update Graph Neural Network for Multi-variate Time Series Anomaly Detection
by: Jo, Hayoung, et al.
Published: (2024)

Skill-Based Mixture-of-Experts: Adaptive Routing for Heterogeneous Reasoning via Inferred Skills
by: Chen, Justin Chih-Yao, et al.
Published: (2025)

Robustness of Mixtures of Experts to Feature Noise
by: Sun, Dong, et al.
Published: (2026)

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

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

Global-Local Graph Neural Networks for Node-Classification
by: Eliasof, Moshe, et al.
Published: (2024)

Towards Invariance to Node Identifiers in Graph Neural Networks
by: Bechler-Speicher, Maya, et al.
Published: (2025)

COMBINEX: A Unified Counterfactual Explainer for Graph Neural Networks via Node Feature and Structural Perturbations
by: Giorgi, Flavio, et al.
Published: (2025)

The Role of Node Features in Graph Pooling
by: von Pichowski, Jan, et al.
Published: (2026)

Enhancing Node-Level Graph Domain Adaptation by Alleviating Local Dependency
by: Tai, Xinwei, et al.
Published: (2025)

Modeling Edge-Specific Node Features through Co-Representation Neural Hypergraph Diffusion
by: Zheng, Yijia, et al.
Published: (2024)

Can Transformers Learn to Verify During Backtracking Search?
by: Phua, Yin Jun, et al.
Published: (2026)

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

Disambiguated Node Classification with Graph Neural Networks
by: Zhao, Tianxiang, et al.
Published: (2024)

Revisiting Edge Perturbation for Graph Neural Network in Graph Data Augmentation and Attack
by: Liu, Xin, et al.
Published: (2024)

From Nodes to Narratives: Explaining Graph Neural Networks with LLMs and Graph Context
by: Baghershahi, Peyman, et al.
Published: (2025)

Preserving Node-level Privacy in Graph Neural Networks
by: Xiang, Zihang, et al.
Published: (2023)

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

Node-level Contrastive Unlearning on Graph Neural Networks
by: Lee, Hong kyu, et al.
Published: (2025)

Parallelizing Node-Level Explainability in Graph Neural Networks
by: Llorente, Oscar, et al.
Published: (2026)

Position-Sensing Graph Neural Networks: Proactively Learning Nodes Relative Positions
by: Qin, Zhenyue, et al.
Published: (2021)

Variational Mixture of Graph Neural Experts for Alzheimer's Disease Biomarker Recognition in EEG Brain Networks
by: Ding, Jun-En, et al.
Published: (2025)

Influence Functions for Edge Edits in Non-Convex Graph Neural Networks
by: Heo, Jaeseung, et al.
Published: (2025)

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

Graph Convolutional Network For Semi-supervised Node Classification With Subgraph Sketching
by: Huang, Zibin, et al.
Published: (2024)

Attacks on Node Attributes in Graph Neural Networks
by: Xu, Ying, et al.
Published: (2024)