Cover Image

LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sun, Li, Huang, Zhenhao, Peng, Hao, Wang, Yujie, Liu, Chunyang, Yu, Philip S.
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ASIL: Augmented Structural Information Learning for Deep Graph Clustering in Hyperbolic Space
by: Sun, Li, et al.
Published: (2025)

Unsupervised Graph Clustering with Deep Structural Entropy
by: Zhang, Jingyun, et al.
Published: (2025)

Spiking Graph Neural Network on Riemannian Manifolds
by: Sun, Li, et al.
Published: (2024)

Hyperbolic Continuous Structural Entropy for Hierarchical Clustering
by: Zeng, Guangjie, et al.
Published: (2025)

Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning
by: Sun, Li, et al.
Published: (2024)

DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing
by: Sun, Li, et al.
Published: (2024)

Pioneer: Physics-informed Riemannian Graph ODE for Entropy-increasing Dynamics
by: Sun, Li, et al.
Published: (2025)

RiemannGFM: Learning a Graph Foundation Model from Riemannian Geometry
by: Sun, Li, et al.
Published: (2025)

RiemannGL: Riemannian Geometry Changes Graph Deep Learning
by: Sun, Li, et al.
Published: (2026)

Heterophily-Agnostic Hypergraph Neural Networks with Riemannian Local Exchanger
by: Sun, Li, et al.
Published: (2026)

Deeper with Riemannian Geometry: Overcoming Oversmoothing and Oversquashing for Graph Foundation Models
by: Sun, Li, et al.
Published: (2025)

Multi-Domain Riemannian Graph Gluing for Building Graph Foundation Models
by: Sun, Li, et al.
Published: (2026)

Differentiable Cluster Graph Neural Network
by: Dong, Yanfei, et al.
Published: (2024)

Rethinking Structure Learning For Graph Neural Networks
by: Zheng, Yilun, et al.
Published: (2024)

Uncertainty in Graph Neural Networks: A Survey
by: Wang, Fangxin, et al.
Published: (2024)

GraphRARE: Reinforcement Learning Enhanced Graph Neural Network with Relative Entropy
by: Peng, Tianhao, et al.
Published: (2023)

Graph Neural Networks for Graphs with Heterophily: A Survey
by: Zheng, Xin, et al.
Published: (2022)

HG-Adapter: Improving Pre-Trained Heterogeneous Graph Neural Networks with Dual Adapters
by: Mo, Yujie, et al.
Published: (2024)

Prompt-based Unifying Inference Attack on Graph Neural Networks
by: Wei, Yuecen, et al.
Published: (2024)

Bounded Graph Clustering with Graph Neural Networks
by: Neocosmos, Kibidi, et al.
Published: (2025)

Bayesian Entropy Neural Networks for Physics-Aware Prediction
by: Rathnakumar, Rahul, et al.
Published: (2024)

Learning Invariant Representations of Graph Neural Networks via Cluster Generalization
by: Xia, Donglin, et al.
Published: (2024)

GCL-GCN: Graphormer and Contrastive Learning Enhanced Attributed Graph Clustering Network
by: Li, Binxiong, et al.
Published: (2025)

Structure-enhanced Contrastive Learning for Graph Clustering
by: Wu, Xunlian, et al.
Published: (2024)

Intrinsic Lorentz Neural Network
by: Shi, Xianglong, et al.
Published: (2026)

MDS-GNN: A Mutual Dual-Stream Graph Neural Network on Graphs with Incomplete Features and Structure
by: Yuan, Peng, et al.
Published: (2024)

Drug Repurposing Using Deep Embedded Clustering and Graph Neural Networks
by: Delzer, Luke, et al.
Published: (2025)

Variational Graph Generator for Multi-View Graph Clustering
by: Chen, Jianpeng, et al.
Published: (2022)

Weighted Graph Clustering via Scale Contraction and Graph Structure Learning
by: Liu, Haobing, et al.
Published: (2026)

Do Graph Neural Networks Work for High Entropy Alloys?
by: Zhang, Hengrui, et al.
Published: (2024)

Probability Passing for Graph Neural Networks: Graph Structure and Representations Joint Learning
by: Wang, Ziyan, et al.
Published: (2024)

Model Based and Physics Informed Deep Learning Neural Network Structures
by: Mohammad-Djafari, Ali, et al.
Published: (2024)

Fast and Geometrically Grounded Lorentz Neural Networks
by: van der Klis, Robert, et al.
Published: (2026)

Deep Temporal Graph Clustering
by: Liu, Meng, et al.
Published: (2023)

A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications
by: Han, Jiaqi, et al.
Published: (2024)

Transfer Entropy in Graph Convolutional Neural Networks
by: Moldovan, Adrian, et al.
Published: (2024)

SpectralNet: Spectral Clustering using Deep Neural Networks
by: Shaham, Uri, et al.
Published: (2018)

Cluster-Enhanced Federated Graph Neural Network for Recommendation
by: Wang, Haiyan, et al.
Published: (2024)

Is Fixing Schema Graphs Necessary? Full-Resolution Graph Structure Learning for Relational Deep Learning
by: Huang, Yi, et al.
Published: (2026)

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