:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhao, Tianqi, Dong, Ngan Thi, Hanjalic, Alan, Khosla, Megha
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2406.12439
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Multi-label Node Classification On Graph-Structured Data
by: Zhao, Tianqi, et al.
Published: (2023)

AGALE: A Graph-Aware Continual Learning Evaluation Framework
by: Zhao, Tianqi, et al.
Published: (2024)

How does Graph Structure Modulate Membership-Inference Risk for Graph Neural Networks?
by: Khosla, Megha
Published: (2026)

GNN-MultiFix: Addressing the pitfalls for GNNs for multi-label node classification
by: Zhao, Tianqi, et al.
Published: (2024)

Draw a Portrait of Your Graph Data: An Instance-Level Profiling Framework for Graph-Structured Data
by: Zhao, Tianqi, et al.
Published: (2025)

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

Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization
by: Xue, Yuan, et al.
Published: (2026)

Population-Scale Network Embeddings Expose Educational Divides in Network Structure Related to Right-Wing Populist Voting
by: Lüken, Malte, et al.
Published: (2025)

Model Selection with Model Zoo via Graph Learning
by: Li, Ziyu, et al.
Published: (2024)

IGNN-Solver: A Graph Neural Solver for Implicit Graph Neural Networks
by: Lin, Junchao, et al.
Published: (2024)

Detecting Anomalous Events in Object-centric Business Processes via Graph Neural Networks
by: Niro, Alessandro, et al.
Published: (2024)

Partial Soft-Matching Distance for Neural Representational Comparison with Partial Unit Correspondence
by: Kapoor, Chaitanya, et al.
Published: (2026)

Can Subgraph Explanations Be Weaponized to Steal Graph Neural Networks?
by: Nimase, Ojas, et al.
Published: (2026)

A Graph Sufficiency Perspective for Neural Networks
by: Shen, Cencheng, et al.
Published: (2025)

Representational Alignment Across Model Layers and Brain Regions with Multi-Level Optimal Transport
by: Shah, Shaan, et al.
Published: (2025)

Data-centric Prompt Tuning for Dynamic Graphs
by: Peng, Yufei, et al.
Published: (2026)

Measuring the Representational Alignment of Neural Systems in Superposition
by: Liu, Sunny, et al.
Published: (2026)

Data-centric Graph Learning: A Survey
by: Guo, Yuxin, et al.
Published: (2023)

Superposition disentanglement of neural representations reveals hidden alignment
by: Longon, André, et al.
Published: (2025)

Applying Ensemble Models based on Graph Neural Network and Reinforcement Learning for Wind Power Forecasting
by: Song, Hongjin, et al.
Published: (2025)

Network Tomography with Path-Centric Graph Neural Network
by: Hu, Yuntong, et al.
Published: (2025)

Temporal Motif Signatures for Temporal Graph Neural Networks
by: Sandfelder, Dylan, et al.
Published: (2026)

Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users
by: Phuong, Thuy Pham Thi, et al.
Published: (2026)

RSTGCN: Railway-centric Spatio-Temporal Graph Convolutional Network for Train Delay Prediction
by: Chowdhury, Koyena, et al.
Published: (2025)

TCGU: Data-centric Graph Unlearning based on Transferable Condensation
by: Li, Fan, et al.
Published: (2024)

Dual-Channel Multiplex Graph Neural Networks for Recommendation
by: Li, Xiang, et al.
Published: (2024)

Barycentric alignment for instance-level comparison of neural representations
by: Saha, Shreya, et al.
Published: (2026)

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

WaterDrum: Watermarking for Data-centric Unlearning Metric
by: Lu, Xinyang, et al.
Published: (2025)

Graph Neural Network Explanations are Fragile
by: Li, Jiate, et al.
Published: (2024)

DoseGNN: Improving the Performance of Deep Learning Models in Adaptive Dose-Volume Histogram Prediction through Graph Neural Networks
by: Dong, Zehao, et al.
Published: (2024)

Interpolation-Split: a data-centric deep learning approach with big interpolated data to boost airway segmentation performance
by: Cheung, Wing Keung, et al.
Published: (2023)

GraphAlign: Pretraining One Graph Neural Network on Multiple Graphs via Feature Alignment
by: Hou, Zhenyu, et al.
Published: (2024)

Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection
by: Dong, Xiangyu, et al.
Published: (2023)

IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks
by: Dong, Yushun, et al.
Published: (2024)

Ignoring Directionality Leads to Compromised Graph Neural Network Explanations
by: Sun, Changsheng, et al.
Published: (2025)

SiGNN: A Spike-induced Graph Neural Network for Dynamic Graph Representation Learning
by: Chen, Dong, et al.
Published: (2024)

A zone-based training approach for last-mile routing using Graph Neural Networks and Pointer Networks
by: Ruiz-Fas, Àngel, et al.
Published: (2026)

TabClustPFN: A Prior-Fitted Network for Tabular Data Clustering
by: Zhao, Tianqi, et al.
Published: (2026)

Certified Defense on the Fairness of Graph Neural Networks
by: Dong, Yushun, et al.
Published: (2023)