Cover Image

Graph Canonical Correlation Analysis

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Park, Hongju, Bai, Shuyang, Ye, Zhenyao, Lee, Hwiyoung, Ma, Tianzhou, Chen, Shuo
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

A Systematic Bias of Machine Learning Regression Models and Its Correction: an Application to Imaging-based Brain Age Prediction
by: Lee, Hwiyoung, et al.
Published: (2024)

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

Preventing Model Collapse in Deep Canonical Correlation Analysis by Noise Regularization
by: He, Junlin, et al.
Published: (2024)

Deep Dynamic Probabilistic Canonical Correlation Analysis
by: Tang, Shiqin, et al.
Published: (2025)

Thompson Sampling in Partially Observable Contextual Bandits
by: Park, Hongju, et al.
Published: (2024)

Optimal Sampling Designs for Multi-dimensional Streaming Time Series with Application to Power Grid Sensor Data
by: Xie, Rui, et al.
Published: (2023)

Nonlinear Sparse Generalized Canonical Correlation Analysis for Multi-view High-dimensional Data
by: Wu, Rong, et al.
Published: (2025)

Permutation Inference for Canonical Correlation Analysis
by: Winkler, Anderson M., et al.
Published: (2020)

Citation Recommendation using Deep Canonical Correlation Analysis
by: McNamara, Conor, et al.
Published: (2025)

The Effect of Alcohol intake on Brain White Matter Microstructural Integrity: A New Causal Inference Framework for Incomplete Phenomic Data
by: Chen, Chixiang, et al.
Published: (2023)

Outcome-Calibrated Regression and Predicted Outcome-Based Inference
by: Lee, Hwiyoung, et al.
Published: (2026)

Subspace Clustering of Subspaces: Unifying Canonical Correlation Analysis and Subspace Clustering
by: Karakasis, Paris A., et al.
Published: (2025)

InfoDPCCA: Information-Theoretic Dynamic Probabilistic Canonical Correlation Analysis
by: Tang, Shiqin, et al.
Published: (2025)

Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability
by: Dong, Zehao, et al.
Published: (2023)

Multiview Canonical Correlation Analysis for Automatic Pathological Speech Detection
by: Kaloga, Yacouba, et al.
Published: (2024)

Behavior Learning (BL): Learning Hierarchical Optimization Structures from Data
by: Ma, Zhenyao, et al.
Published: (2026)

Modeling Dependence in Omics Association Analysis via Structured Co-Expression Networks to Improve Power and Replicability
by: Lee, Hwiyoung, et al.
Published: (2025)

Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis
by: Horoi, Stefan, et al.
Published: (2024)

Canonical-Correlation-Based Fast Feature Selection for Structural Health Monitoring
by: Zhang, Sikai, et al.
Published: (2021)

Canonical Correlation Guided Deep Neural Network
by: Chen, Zhiwen, et al.
Published: (2024)

Directed Acyclic Graph Structure Learning from Dynamic Graphs
by: Fan, Shaohua, et al.
Published: (2022)

Neural Canonical Polyadic Factorization for Traffic Analysis
by: Luo, Wenyu, et al.
Published: (2025)

Sparse Autoencoders Do Not Find Canonical Units of Analysis
by: Leask, Patrick, et al.
Published: (2025)

Trustworthy AI/ML Regression and Unbiased Causal Inference for Real-World Data
by: Xu, Yifei, et al.
Published: (2026)

Scalable Geometric Learning with Correlation-Based Functional Brain Networks
by: You, Kisung, et al.
Published: (2025)

Self-supervised Adversarial Purification for Graph Neural Networks
by: Lee, Woohyun, et al.
Published: (2026)

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

Temporal Graph Learning Recurrent Neural Network for Traffic Forecasting
by: Lee, Sanghyun, et al.
Published: (2024)

Predicting Liquidity Coverage Ratio with Gated Recurrent Units: A Deep Learning Model for Risk Management
by: Xu, Zhen, et al.
Published: (2024)

Beyond Unconstrained Features: Neural Collapse for Shallow Neural Networks with General Data
by: Hong, Wanli, et al.
Published: (2024)

Mixture of Experts (MoE): A Big Data Perspective
by: Gan, Wensheng, et al.
Published: (2025)

Generalized Orthogonal Procrustes Problem under Arbitrary Adversaries
by: Ling, Shuyang
Published: (2021)

Exploring Correlations of Self-Supervised Tasks for Graphs
by: Fang, Taoran, et al.
Published: (2024)

Dynamic Graph Transformer with Correlated Spatial-Temporal Positional Encoding
by: Wang, Zhe, et al.
Published: (2024)

Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding
by: Ma, Jiangyan, et al.
Published: (2023)

GraphSPNs: Sum-Product Networks Benefit From Canonical Orderings
by: Papež, Milan, et al.
Published: (2024)

Sliding Window Informative Canonical Correlation Analysis
by: Prasadan, Arvind
Published: (2025)

Modeling Inter-Intra Heterogeneity for Graph Federated Learning
by: Yu, Wentao, et al.
Published: (2024)

Heterogeneity-Aware Knowledge Sharing for Graph Federated Learning
by: Yu, Wentao, et al.
Published: (2026)

GEN: A Practical Alternative to Graph Transformers for Long-Range Graph Modeling
by: Wang, Shuo, et al.
Published: (2024)