Copertina

Layer-diverse Negative Sampling for Graph Neural Networks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Duan, Wei, Lu, Jie, Wang, Yu Guang, Xuan, Junyu
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Inferring Latent Temporal Sparse Coordination Graph for Multi-Agent Reinforcement Learning
di: Duan, Wei, et al.
Pubblicazione: (2024)

Bayesian Ego-graph Inference for Networked Multi-Agent Reinforcement Learning
di: Duan, Wei, et al.
Pubblicazione: (2025)

Group-Aware Coordination Graph for Multi-Agent Reinforcement Learning
di: Duan, Wei, et al.
Pubblicazione: (2024)

Functional Stochastic Gradient MCMC for Bayesian Neural Networks
di: Wu, Mengjing, et al.
Pubblicazione: (2024)

Heterogeneous Information-Bottleneck Coordination Graphs for Multi-Agent Reinforcement Learning
di: Duan, Wei, et al.
Pubblicazione: (2026)

Bandwidth-constrained Variational Message Encoding for Cooperative Multi-agent Reinforcement Learning
di: Duan, Wei, et al.
Pubblicazione: (2025)

LSTM Autoencoder-based Deep Neural Networks for Barley Genotype-to-Phenotype Prediction
di: Wang, Guanjin, et al.
Pubblicazione: (2024)

Commute Graph Neural Networks
di: Zhuo, Wei, et al.
Pubblicazione: (2024)

Neighborhood Sampling Does Not Learn the Same Graph Neural Network
di: Niu, Zehao, et al.
Pubblicazione: (2025)

Graph Neural Networks with Feature and Structure Aware Random Walk
di: Zhuo, Wei, et al.
Pubblicazione: (2021)

RSEA-MVGNN: Multi-View Graph Neural Network with Reliable Structural Enhancement and Aggregation
di: Chen, Junyu, et al.
Pubblicazione: (2024)

Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks
di: Wang, Puyu, et al.
Pubblicazione: (2023)

Personalized Layer Selection for Graph Neural Networks
di: Sharma, Kartik, et al.
Pubblicazione: (2025)

Efficient Link Prediction via GNN Layers Induced by Negative Sampling
di: Wang, Yuxin, et al.
Pubblicazione: (2023)

Dynamic Localisation of Spatial-Temporal Graph Neural Network
di: Duan, Wenying, et al.
Pubblicazione: (2025)

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

Contrastive Learning with Negative Sampling Correction
di: Wang, Lu, et al.
Pubblicazione: (2024)

A Behavior-Aware Approach for Deep Reinforcement Learning in Non-stationary Environments without Known Change Points
di: Liu, Zihe, et al.
Pubblicazione: (2024)

Does GCL Need a Large Number of Negative Samples? Enhancing Graph Contrastive Learning with Effective and Efficient Negative Sampling
di: Huang, Yongqi, et al.
Pubblicazione: (2025)

NoiseHGNN: Synthesized Similarity Graph-Based Neural Network For Noised Heterogeneous Graph Representation Learning
di: Zhang, Xiong, et al.
Pubblicazione: (2024)

Layer-to-Layer Knowledge Mixing in Graph Neural Network for Chemical Property Prediction
di: See, Teng Jiek, et al.
Pubblicazione: (2025)

SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks
di: Zhuang, Dingyi, et al.
Pubblicazione: (2024)

Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks
di: Peng, Jie, et al.
Pubblicazione: (2024)

Hard Negative Sample-Augmented DPO Post-Training for Small Language Models
di: Lu, Haocheng, et al.
Pubblicazione: (2025)

Heterogeneous Graph Contrastive Learning with Meta-path Contexts and Adaptively Weighted Negative Samples
di: Yu, Jianxiang, et al.
Pubblicazione: (2022)

Faithful Interpretation for Graph Neural Networks
di: Hu, Lijie, et al.
Pubblicazione: (2024)

Sampling Transferable Graph Neural Networks with Limited Graph Information
di: Wang, Haoyu, et al.
Pubblicazione: (2024)

UQGNN: Uncertainty Quantification of Graph Neural Networks for Multivariate Spatiotemporal Prediction
di: Yu, Dahai, et al.
Pubblicazione: (2025)

AGS-GNN: Attribute-guided Sampling for Graph Neural Networks
di: Das, Siddhartha Shankar, et al.
Pubblicazione: (2024)

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks
di: Younesian, Taraneh, et al.
Pubblicazione: (2023)

Are LLM-Enhanced Graph Neural Networks Robust against Poisoning Attacks?
di: Ma, Yuhang, et al.
Pubblicazione: (2026)

Layer Embedding Deep Fusion Graph Neural Network
di: Xu, Taihua, et al.
Pubblicazione: (2026)

A Generalized Tikhonov Layer for Interpretable-by-design Graph Neural Networks
di: Tremblay, Nicolas, et al.
Pubblicazione: (2026)

Variational Inference on the Final-Layer Output of Neural Networks
di: Wei, Yadi, et al.
Pubblicazione: (2023)

LSPI: Heterogeneous Graph Neural Network Classification Aggregation Algorithm Based on Size Neighbor Path Identification
di: Zhao, Yufei, et al.
Pubblicazione: (2024)

ResRL: Boosting LLM Reasoning via Negative Sample Projection Residual Reinforcement Learning
di: Lin, Zihan, et al.
Pubblicazione: (2026)

Theoretical Learning Performance of Graph Neural Networks: The Impact of Jumping Connections and Layer-wise Sparsification
di: Sun, Jiawei, et al.
Pubblicazione: (2025)

Saliency-Aware Regularized Graph Neural Network
di: Pei, Wenjie, et al.
Pubblicazione: (2024)

Enhancing Spectral Graph Neural Networks with LLM-Predicted Homophily
di: Lu, Kangkang, et al.
Pubblicazione: (2025)

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