Cover Image

REGE: A Method for Incorporating Uncertainty in Graph Embeddings

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Shafi, Zohair, Savcisens, Germans, Eliassi-Rad, Tina
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

The Trilemma of Truth in Large Language Models
by: Savcisens, Germans, et al.
Published: (2025)

Generating Human Understandable Explanations for Node Embeddings
by: Shafi, Zohair, et al.
Published: (2024)

Graph-SCP: Accelerating Set Cover Problems with Graph Neural Networks
by: Shafi, Zohair, et al.
Published: (2023)

FORGE: Foundational Optimization Representations from Graph Embeddings
by: Shafi, Zohair, et al.
Published: (2025)

Representational and Behavioral Stability of Truth in Large Language Models
by: Dies, Samantha, et al.
Published: (2025)

Using Sequences of Life-events to Predict Human Lives
by: Savcisens, Germans, et al.
Published: (2023)

Bypassing Skip-Gram Negative Sampling: Dimension Regularization as a More Efficient Alternative for Graph Embeddings
by: Liu, David, et al.
Published: (2024)

A Misclassification Network-Based Method for Comparative Genomic Analysis
by: He, Wan, et al.
Published: (2024)

tab2seq: A Python Package for Table-to-Sequence Conversion
by: Savcisens, Germans
Published: (2026)

tab2seq: A Python Package for Table-to-Sequence Conversion
by: Savcisens, Germans
Published: (2026)

tab2seq: A Python Package for Table-to-Sequence Conversion
by: Savcisens, Germans
Published: (2026)

When Collaborative Filtering is not Collaborative: Unfairness of PCA for Recommendations
by: Liu, David, et al.
Published: (2023)

Forecasting Faculty Placement from Patterns in Co-authorship Networks
by: Dies, Samantha, et al.
Published: (2025)

When do neural ordinary differential equations generalize on complex networks?
by: Laber, Moritz, et al.
Published: (2026)

Defense Against Shortest Path Attacks
by: Miller, Benjamin A., et al.
Published: (2023)

Hypergraph Representations of scRNA-seq Data for Improved Clustering with Random Walks
by: He, Wan, et al.
Published: (2025)

DeepWeightFlow: Re-Basined Flow Matching for Generating Neural Network Weights
by: Gupta, Saumya, et al.
Published: (2026)

EnvId: A Metric Learning Approach for Forensic Few-Shot Identification of Unseen Environments
by: Moussa, Denise, et al.
Published: (2024)

Decomposing Uncertainty in Probabilistic Knowledge Graph Embeddings: Why Entity Variance Is Not Enough
by: Lee, Chorok
Published: (2025)

Uncertainty-driven Embedding Convolution
by: Lim, Sungjun, et al.
Published: (2025)

A Survey on Recent Random Walk-based Methods for Embedding Knowledge Graphs
by: Bozorgi, Elika, et al.
Published: (2024)

A Survey on Signed Graph Embedding: Methods and Applications
by: Ghosh, Shrabani
Published: (2024)

Incorporating Fairness in Neighborhood Graphs for Fair Spectral Clustering
by: Moorthy, Adithya K, et al.
Published: (2025)

Subspace Projection Methods for Fast Spectral Embeddings of Evolving Graphs
by: Eini, Mohammad, et al.
Published: (2026)

Comparative Analysis of the Land Use and Land Cover Changes in Different Governorates of Oman using Spatiotemporal Multi-spectral Satellite Data
by: Shafi, Muhammad, et al.
Published: (2025)

A Survey on Knowledge Graph Structure and Knowledge Graph Embeddings
by: Sardina, Jeffrey, et al.
Published: (2024)

Hub-aware Random Walk Graph Embedding Methods for Classification
by: Tomčić, Aleksandar, et al.
Published: (2022)

Incorporating Heterophily into Graph Neural Networks for Graph Classification
by: Yang, Jiayi, et al.
Published: (2022)

Practicable Black-box Evasion Attacks on Link Prediction in Dynamic Graphs -- A Graph Sequential Embedding Method
by: Li, Jiate, et al.
Published: (2024)

Uncertainty for Active Learning on Graphs
by: Fuchsgruber, Dominik, et al.
Published: (2024)

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

Uncertainty Quantification on Graph Learning: A Survey
by: Chen, Chao, et al.
Published: (2024)

A Survey on Hypergraph Mining: Patterns, Tools, and Generators
by: Lee, Geon, et al.
Published: (2024)

Resilience in Knowledge Graph Embeddings
by: Sharma, Arnab, et al.
Published: (2024)

A Cryptographic Perspective on Mitigation vs. Detection in Machine Learning
by: Gluch, Greg, et al.
Published: (2025)

$k$-Graph: A Graph Embedding for Interpretable Time Series Clustering
by: Boniol, Paul, et al.
Published: (2025)

REGE Revista de Gestão
Published: (2018)

Uncertainty-Aware Graph Structure Learning
by: Han, Shen, et al.
Published: (2025)

A Survey on Uncertainty Quantification Methods for Deep Learning
by: He, Wenchong, et al.
Published: (2023)

Self-Supervised Graph Embedding Clustering
by: Li, Fangfang, et al.
Published: (2024)