A Deep Latent Space Model for Graph Representation Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Yang, Hanxuan, Kong, Qingchao, Mao, Wenji |
|---|---|
| Format: | Preprint |
| Published: |
2021
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Variational Graph Auto-Encoder Based Inductive Learning Method for Semi-Supervised Classification
by: Yang, Hanxuan, et al.
Published: (2024)
by: Yang, Hanxuan, et al.
Published: (2024)
View Space: Learning Representation across Arbitrary Graphs
by: Lee, Dooho, et al.
Published: (2025)
by: Lee, Dooho, et al.
Published: (2025)
Latent Matters: Learning Deep State-Space Models
by: Klushyn, Alexej, et al.
Published: (2026)
by: Klushyn, Alexej, et al.
Published: (2026)
A Knowledge Enhanced Learning and Semantic Composition Model for Multi-Claim Fact Checking
by: Wang, Shuai, et al.
Published: (2021)
by: Wang, Shuai, et al.
Published: (2021)
scDD: Latent Codes Based scRNA-seq Dataset Distillation with Foundation Model Knowledge
by: Yu, Zhen, et al.
Published: (2025)
by: Yu, Zhen, et al.
Published: (2025)
Multicalibration Boosting: Theory, Convergence, and Transferability
by: Ye, Hanxuan, et al.
Published: (2026)
by: Ye, Hanxuan, et al.
Published: (2026)
RECOVAR: Representation Covariances on Deep Latent Spaces for Seismic Event Detection
by: Efe, Onur, et al.
Published: (2024)
by: Efe, Onur, et al.
Published: (2024)
Evaluating the Stability of Deep Learning Latent Feature Spaces
by: Mabadeje, Ademide O., et al.
Published: (2024)
by: Mabadeje, Ademide O., et al.
Published: (2024)
Graph State-Space Models and Latent Relational Inference
by: Zambon, Daniele, et al.
Published: (2023)
by: Zambon, Daniele, et al.
Published: (2023)
Feature-Space Smoothing: Certified Robustness of Deep Representations
by: Xia, Song, et al.
Published: (2026)
by: Xia, Song, et al.
Published: (2026)
Isometric Representation Learning for Disentangled Latent Space of Diffusion Models
by: Hahm, Jaehoon, et al.
Published: (2024)
by: Hahm, Jaehoon, et al.
Published: (2024)
Refining Latent Representations: A Generative SSL Approach for Heterogeneous Graph Learning
by: Hu, Yulan, et al.
Published: (2023)
by: Hu, Yulan, et al.
Published: (2023)
Alternatives of Unsupervised Representations of Variables on the Latent Space
by: Glushkovsky, Alex
Published: (2024)
by: Glushkovsky, Alex
Published: (2024)
Quantification via Gaussian Latent Space Representations
by: Pérez-Mon, Olaya, et al.
Published: (2025)
by: Pérez-Mon, Olaya, et al.
Published: (2025)
Latent Space Representations of Neural Algorithmic Reasoners
by: Mirjanić, Vladimir V., et al.
Published: (2023)
by: Mirjanić, Vladimir V., et al.
Published: (2023)
Latent Space Energy-based Neural ODEs
by: Cheng, Sheng, et al.
Published: (2024)
by: Cheng, Sheng, et al.
Published: (2024)
Exploring Representation-Aligned Latent Space for Better Generation
by: Xu, Wanghan, et al.
Published: (2025)
by: Xu, Wanghan, et al.
Published: (2025)
Advancing Generalization in PINNs through Latent-Space Representations
by: Wang, Honghui, et al.
Published: (2024)
by: Wang, Honghui, et al.
Published: (2024)
Deep Fair Learning: A Unified Framework for Fine-tuning Representations with Sufficient Networks
by: Shi, Enze, et al.
Published: (2025)
by: Shi, Enze, et al.
Published: (2025)
Improving Intrusion Detection with Domain-Invariant Representation Learning in Latent Space
by: Roy, Padmaksha, et al.
Published: (2023)
by: Roy, Padmaksha, et al.
Published: (2023)
EEGDM: Learning EEG Representation with Latent Diffusion Model
by: Wang, Shaocong, et al.
Published: (2025)
by: Wang, Shaocong, et al.
Published: (2025)
HyReaL: Clustering Attributed Graph via Hyper-Complex Space Representation Learning
by: Chen, Junyang, et al.
Published: (2024)
by: Chen, Junyang, et al.
Published: (2024)
From Performance to Viability: A Bootstrap Framework for Latent-Space Representation Learning in Adaptive Biological Systems
by: Raynal, Jacques, et al.
Published: (2026)
by: Raynal, Jacques, et al.
Published: (2026)
LNN-PINN: A Unified Physics-Only Training Framework with Liquid Residual Blocks
by: Tao, Ze, et al.
Published: (2025)
by: Tao, Ze, et al.
Published: (2025)
Graph Community Augmentation with GMM-based Modeling in Latent Space
by: Fukushima, Shintaro, et al.
Published: (2024)
by: Fukushima, Shintaro, et al.
Published: (2024)
The Latent Space Hypothesis: Toward Universal Medical Representation Learning
by: Patel, Salil
Published: (2025)
by: Patel, Salil
Published: (2025)
Deep Reinforcement Learning-Based DRAM Equalizer Parameter Optimization Using Latent Representations
by: Usama, Muhammad, et al.
Published: (2025)
by: Usama, Muhammad, et al.
Published: (2025)
Learning Ordered Representations in Latent Space for Intrinsic Dimension Estimation via Principal Component Autoencoder
by: Zhan, Qipeng, et al.
Published: (2026)
by: Zhan, Qipeng, et al.
Published: (2026)
Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference
by: Kong, Deqian, et al.
Published: (2024)
by: Kong, Deqian, et al.
Published: (2024)
Toward Learning Latent-Variable Representations of Microstructures by Optimizing in Spatial Statistics Space
by: Hashemi, Sayed Sajad, et al.
Published: (2024)
by: Hashemi, Sayed Sajad, et al.
Published: (2024)
Latent Graph Learning in Generative Models of Neural Signals
by: Kodama, Nathan X., et al.
Published: (2025)
by: Kodama, Nathan X., et al.
Published: (2025)
A Comprehensive Survey on Deep Graph Representation Learning
by: Ju, Wei, et al.
Published: (2023)
by: Ju, Wei, et al.
Published: (2023)
Uncovering the Latent Potential of Deep Intermediate Representations
by: Batra, Arnesh, et al.
Published: (2026)
by: Batra, Arnesh, et al.
Published: (2026)
Causal Structure Representation Learning of Confounders in Latent Space for Recommendation
by: Xu, Hangtong, et al.
Published: (2023)
by: Xu, Hangtong, et al.
Published: (2023)
Relative Representations of Latent Spaces enable Efficient Semantic Channel Equalization
by: Hüttebräucker, Tomás, et al.
Published: (2024)
by: Hüttebräucker, Tomás, et al.
Published: (2024)
Metric Space Magnitude for Evaluating the Diversity of Latent Representations
by: Limbeck, Katharina, et al.
Published: (2023)
by: Limbeck, Katharina, et al.
Published: (2023)
Fairness-Aware Graph Representation Learning with Limited Demographic Information
by: Wang, Zichong, et al.
Published: (2025)
by: Wang, Zichong, et al.
Published: (2025)
Graph Evidential Learning for Anomaly Detection
by: Wei, Chunyu, et al.
Published: (2025)
by: Wei, Chunyu, et al.
Published: (2025)
Dynamic Latent Separation for Deep Learning
by: Tuan, Yi-Lin, et al.
Published: (2022)
by: Tuan, Yi-Lin, et al.
Published: (2022)
Latent Space Symmetry Discovery
by: Yang, Jianke, et al.
Published: (2023)
by: Yang, Jianke, et al.
Published: (2023)
Similar Items
-
Variational Graph Auto-Encoder Based Inductive Learning Method for Semi-Supervised Classification
by: Yang, Hanxuan, et al.
Published: (2024) -
View Space: Learning Representation across Arbitrary Graphs
by: Lee, Dooho, et al.
Published: (2025) -
Latent Matters: Learning Deep State-Space Models
by: Klushyn, Alexej, et al.
Published: (2026) -
A Knowledge Enhanced Learning and Semantic Composition Model for Multi-Claim Fact Checking
by: Wang, Shuai, et al.
Published: (2021) -
scDD: Latent Codes Based scRNA-seq Dataset Distillation with Foundation Model Knowledge
by: Yu, Zhen, et al.
Published: (2025)