Cover Image

Graph Neural Networks Powered by Encoder Embedding for Improved Node Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Shiyu, Shen, Cencheng, Park, Youngser, Priebe, Carey E.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Graph Encoder Ensemble for Simultaneous Vertex Embedding and Community Detection
by: Shen, Cencheng, et al.
Published: (2023)

Principal Graph Encoder Embedding and Principal Community Detection
by: Shen, Cencheng, et al.
Published: (2025)

One-Hot Graph Encoder Embedding
by: Shen, Cencheng, et al.
Published: (2021)

Discovering Communication Pattern Shifts in Large-Scale Labeled Networks using Encoder Embedding and Vertex Dynamics
by: Shen, Cencheng, et al.
Published: (2023)

Edge-Parallel Graph Encoder Embedding
by: Lubonja, Ariel, et al.
Published: (2024)

Synergistic Graph Fusion via Encoder Embedding
by: Shen, Cencheng, et al.
Published: (2023)

On the Incommensurability Phenomenon
by: Fishkind, Donniell E., et al.
Published: (2013)

Encoder Embedding for General Graph and Node Classification
by: Shen, Cencheng
Published: (2024)

Refined Graph Encoder Embedding via Self-Training and Latent Community Recovery
by: Shen, Cencheng, et al.
Published: (2024)

Decision Tree Embedding by Leaf-Means
by: Shen, Cencheng, et al.
Published: (2025)

From Distance Correlation to Multiscale Graph Correlation
by: Shen, Cencheng, et al.
Published: (2017)

A Simple Spectral Failure Mode for Graph Convolutional Networks
by: Priebe, Carey E., et al.
Published: (2020)

Manifold Matching using Shortest-Path Distance and Joint Neighborhood Selection
by: Shen, Cencheng, et al.
Published: (2014)

Efficient Graph Encoder Embedding for Large Sparse Graphs in Python
by: Qin, Xihan, et al.
Published: (2024)

Explaining Categorical Feature Interactions Using Graph Covariance and LLMs
by: Shen, Cencheng, et al.
Published: (2025)

Robust Vertex Classification
by: Chen, Li, et al.
Published: (2013)

Concentration bounds on response-based vector embeddings of black-box generative models
by: Acharyya, Aranyak, et al.
Published: (2025)

Sparse Representation Classification Beyond L1 Minimization and the Subspace Assumption
by: Shen, Cencheng, et al.
Published: (2015)

Generalized Canonical Correlation Analysis for Classification
by: Shen, Cencheng, et al.
Published: (2013)

Statistical inference on black-box generative models in the data kernel perspective space
by: Helm, Hayden, et al.
Published: (2024)

Fast and Scalable Multi-Kernel Encoder Classifier
by: Shen, Cencheng
Published: (2024)

Semisupervised regression in latent structure networks on unknown manifolds
by: Acharyya, Aranyak, et al.
Published: (2023)

A Graph Sufficiency Perspective for Neural Networks
by: Shen, Cencheng, et al.
Published: (2025)

Discovering and Deciphering Relationships Across Disparate Data Modalities
by: Vogelstein, Joshua T., et al.
Published: (2016)

Universally Consistent K-Sample Tests via Dependence Measures
by: Panda, Sambit, et al.
Published: (2019)

Optimizing the Induced Correlation in Omnibus Joint Graph Embeddings
by: Pantazis, Konstantinos, et al.
Published: (2024)

Out-of-Sample Embedding with Proximity Data: Projection versus Restricted Reconstruction
by: Trosset, Michael W., et al.
Published: (2025)

Data Kernel Perspective Space Performance Guarantees for Synthetic Data from Transformer Models
by: Browder, Michael, et al.
Published: (2026)

Black-box model classification under the discriminative factorization
by: Helm, Hayden, et al.
Published: (2026)

Continuous Multidimensional Scaling
by: Trosset, Michael W., et al.
Published: (2024)

TinyGraph: Joint Feature and Node Condensation for Graph Neural Networks
by: Liu, Yezi, et al.
Published: (2024)

Network Dependence Testing via Diffusion Maps and Distance-Based Correlations
by: Lee, Youjin, et al.
Published: (2017)

The Exact Equivalence of Distance and Kernel Methods for Hypothesis Testing
by: Shen, Cencheng, et al.
Published: (2018)

Learning Interpretable Characteristic Kernels via Decision Forests
by: Panda, Sambit, et al.
Published: (2018)

Linear Discriminant Analysis with Gradient Optimization
by: Shen, Cencheng, et al.
Published: (2025)

High-Dimensional Independence Testing via Maximum and Average Distance Correlations
by: Shen, Cencheng, et al.
Published: (2020)

Comparing Foundation Models using Data Kernels
by: Duderstadt, Brandon, et al.
Published: (2023)

Euclidean mirrors and dynamics in network time series
by: Athreya, Avanti, et al.
Published: (2022)

Random line graphs and edge-attributed network inference
by: Lubberts, Zachary, et al.
Published: (2021)

Tracking the perspectives of interacting language models
by: Helm, Hayden, et al.
Published: (2024)