Saved in:
| Main Authors: | Dong, Yushun, Zhang, Binchi, Lei, Zhenyu, Zou, Na, Li, Jundong |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.19398 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Towards Certified Unlearning for Deep Neural Networks
by: Zhang, Binchi, et al.
Published: (2024)
by: Zhang, Binchi, et al.
Published: (2024)
Certified Defense on the Fairness of Graph Neural Networks
by: Dong, Yushun, et al.
Published: (2023)
by: Dong, Yushun, et al.
Published: (2023)
Adversarial Attacks on Fairness of Graph Neural Networks
by: Zhang, Binchi, et al.
Published: (2023)
by: Zhang, Binchi, et al.
Published: (2023)
GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
by: Fu, Xingbo, et al.
Published: (2025)
by: Fu, Xingbo, et al.
Published: (2025)
Federated Graph Learning with Graphless Clients
by: Fu, Xingbo, et al.
Published: (2024)
by: Fu, Xingbo, et al.
Published: (2024)
Verification of Machine Unlearning is Fragile
by: Zhang, Binchi, et al.
Published: (2024)
by: Zhang, Binchi, et al.
Published: (2024)
ST-FiT: Inductive Spatial-Temporal Forecasting with Limited Training Data
by: Lei, Zhenyu, et al.
Published: (2024)
by: Lei, Zhenyu, et al.
Published: (2024)
Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective
by: Dong, Yushun, et al.
Published: (2024)
by: Dong, Yushun, et al.
Published: (2024)
Safety in Graph Machine Learning: Threats and Safeguards
by: Wang, Song, et al.
Published: (2024)
by: Wang, Song, et al.
Published: (2024)
A Benchmark for Fairness-Aware Graph Learning
by: Dong, Yushun, et al.
Published: (2024)
by: Dong, Yushun, et al.
Published: (2024)
Harnessing Large Language Models for Disaster Management: A Survey
by: Lei, Zhenyu, et al.
Published: (2025)
by: Lei, Zhenyu, et al.
Published: (2025)
Federated Graph Learning with Structure Proxy Alignment
by: Fu, Xingbo, et al.
Published: (2024)
by: Fu, Xingbo, et al.
Published: (2024)
MolEdit: Knowledge Editing for Multimodal Molecule Language Models
by: Lei, Zhenyu, et al.
Published: (2025)
by: Lei, Zhenyu, et al.
Published: (2025)
Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model Fusion
by: Zhang, Binchi, et al.
Published: (2025)
by: Zhang, Binchi, et al.
Published: (2025)
Certified Unlearning for Neural Networks
by: Koloskova, Anastasia, et al.
Published: (2025)
by: Koloskova, Anastasia, et al.
Published: (2025)
PRUNE: A Patching Based Repair Framework for Certifiable Unlearning of Neural Networks
by: Li, Xuran, et al.
Published: (2025)
by: Li, Xuran, et al.
Published: (2025)
CREDIT: Certified Ownership Verification of Deep Neural Networks Against Model Extraction Attacks
by: Shen, Bolin, et al.
Published: (2026)
by: Shen, Bolin, et al.
Published: (2026)
FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs
by: Chen, Zihan, et al.
Published: (2025)
by: Chen, Zihan, et al.
Published: (2025)
Can Subgraph Explanations Be Weaponized to Steal Graph Neural Networks?
by: Nimase, Ojas, et al.
Published: (2026)
by: Nimase, Ojas, et al.
Published: (2026)
Interpretable Neuropsychiatric Diagnosis via Concept-Guided Graph Neural Networks
by: Wang, Song, et al.
Published: (2025)
by: Wang, Song, et al.
Published: (2025)
Certified Signed Graph Unlearning
by: Zhao, Junpeng, et al.
Published: (2025)
by: Zhao, Junpeng, et al.
Published: (2025)
Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning
by: Fu, Xingbo, et al.
Published: (2024)
by: Fu, Xingbo, et al.
Published: (2024)
ATOM: A Framework of Detecting Query-Based Model Extraction Attacks for Graph Neural Networks
by: Cheng, Zhan, et al.
Published: (2025)
by: Cheng, Zhan, et al.
Published: (2025)
Edge Prompt Tuning for Graph Neural Networks
by: Fu, Xingbo, et al.
Published: (2025)
by: Fu, Xingbo, et al.
Published: (2025)
Rethinking Fair Graph Neural Networks from Re-balancing
by: Li, Zhixun, et al.
Published: (2024)
by: Li, Zhixun, et al.
Published: (2024)
Adaptive Dual Prompting: Hierarchical Debiasing for Fairness-aware Graph Neural Networks
by: Yang, Yuhan, et al.
Published: (2025)
by: Yang, Yuhan, et al.
Published: (2025)
Spectral Greedy Coresets for Graph Neural Networks
by: Ding, Mucong, et al.
Published: (2024)
by: Ding, Mucong, et al.
Published: (2024)
Towards Quantifying the Hessian Structure of Neural Networks
by: Dong, Zhaorui, et al.
Published: (2025)
by: Dong, Zhaorui, et al.
Published: (2025)
Resolving Editing-Unlearning Conflicts: A Knowledge Codebook Framework for Large Language Model Updating
by: Zhang, Binchi, et al.
Published: (2025)
by: Zhang, Binchi, et al.
Published: (2025)
CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models
by: Wang, Song, et al.
Published: (2024)
by: Wang, Song, et al.
Published: (2024)
Exploring and Improving Initialization for Deep Graph Neural Networks: A Signal Propagation Perspective
by: Wang, Senmiao, et al.
Published: (2025)
by: Wang, Senmiao, et al.
Published: (2025)
Gaussian Certified Unlearning in High Dimensions: A Hypothesis Testing Approach
by: Pandey, Aaradhya, et al.
Published: (2025)
by: Pandey, Aaradhya, et al.
Published: (2025)
Scalable and Certifiable Graph Unlearning: Overcoming the Approximation Error Barrier
by: Yi, Lu, et al.
Published: (2024)
by: Yi, Lu, et al.
Published: (2024)
GraphIP-Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It?
by: Zhao, Kaixiang, et al.
Published: (2026)
by: Zhao, Kaixiang, et al.
Published: (2026)
Attack by Unlearning: Unlearning-Induced Adversarial Attacks on Graph Neural Networks
by: Zhang, Jiahao, et al.
Published: (2026)
by: Zhang, Jiahao, et al.
Published: (2026)
Node-level Contrastive Unlearning on Graph Neural Networks
by: Lee, Hong kyu, et al.
Published: (2025)
by: Lee, Hong kyu, et al.
Published: (2025)
Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective for Molecular Property Prediction
by: He, Yinhan, et al.
Published: (2024)
by: He, Yinhan, et al.
Published: (2024)
Fully Decentralized Certified Unlearning
by: Lamri, Hithem, et al.
Published: (2025)
by: Lamri, Hithem, et al.
Published: (2025)
Relating-Up: Advancing Graph Neural Networks through Inter-Graph Relationships
by: Zou, Qi, et al.
Published: (2024)
by: Zou, Qi, et al.
Published: (2024)
GraphAlign: Pretraining One Graph Neural Network on Multiple Graphs via Feature Alignment
by: Hou, Zhenyu, et al.
Published: (2024)
by: Hou, Zhenyu, et al.
Published: (2024)
Similar Items
-
Towards Certified Unlearning for Deep Neural Networks
by: Zhang, Binchi, et al.
Published: (2024) -
Certified Defense on the Fairness of Graph Neural Networks
by: Dong, Yushun, et al.
Published: (2023) -
Adversarial Attacks on Fairness of Graph Neural Networks
by: Zhang, Binchi, et al.
Published: (2023) -
GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
by: Fu, Xingbo, et al.
Published: (2025) -
Federated Graph Learning with Graphless Clients
by: Fu, Xingbo, et al.
Published: (2024)