Generalized canonical correlation analysis for classification. - Cencheng Shen; Ming Sun; Minh Tang; Carey E. Priebe (J. Multivar. Anal., 2014)

Collaborative Information Retrieval Framework Based on FCA. - Wenyan Bao; Cencheng Shen; Yun Li 010 (IEEE WISA, 2015)

On the Incommensurability Phenomenon. - Donniell E. Fishkind; Cencheng Shen; Youngser Park; Carey E. Priebe (J. Classif., 2016)

Robust Vertex Classification. - Li Chen; Cencheng Shen; Joshua T. Vogelstein; Carey E. Priebe (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Manifold matching using shortest-path distance and joint neighborhood selection. - Cencheng Shen; Joshua T. Vogelstein; Carey E. Priebe (Pattern Recognit. Lett., 2017)

The Exact Equivalence of Distance and Kernel Methods for Hypothesis Testing. - Cencheng Shen; Joshua T. Vogelstein (CoRR, 2018)

Decision Forests Induce Characteristic Kernels. - Cencheng Shen; Joshua T. Vogelstein (CoRR, 2018)

Sparse Representation Classification via Screening for Graphs. - Cencheng Shen; Li Chen; Yuexiao Dong; Carey E. Priebe (CoRR, 2019)

Estimating Information-Theoretic Quantities with Random Forests. - Richard Guo; Cencheng Shen; Joshua T. Vogelstein (CoRR, 2019)

mgcpy: A Comprehensive High Dimensional Independence Testing Python Package. - Sambit Panda; Satish Palaniappan; Junhao Xiong; Ananya Swaminathan; Sandhya Ramachandran; Eric W. Bridgeford; Cencheng Shen; Joshua T. Vogelstein (CoRR, 2019)

A Consistent Independence Test for Multivariate Time-Series. - Ronak D. Mehta; Cencheng Shen; Ting Xu 001; Joshua T. Vogelstein (CoRR, 2019)

The Exact Equivalence of Independence Testing and Two-Sample Testing. - Cencheng Shen; Carey E. Priebe; Joshua T. Vogelstein (CoRR, 2019)

The Chi-Square Test of Distance Correlation. - Cencheng Shen; Joshua T. Vogelstein (CoRR, 2019)

High-Dimensional Independence Testing and Maximum Marginal Correlation. - Cencheng Shen (CoRR, 2020)

Sparse Projection Oblique Randomer Forests. - Tyler M. Tomita; James Browne; Cencheng Shen; Jaewon Chung; Jesse Patsolic; Benjamin Falk; Carey E. Priebe; Jason Yim; Randal C. Burns; Mauro Maggioni; Joshua T. Vogelstein (J. Mach. Learn. Res., 2020)

Sparse Representation Classification Beyond ℓ1 Minimization and the Subspace Assumption. - Cencheng Shen; Li Chen; Yuexiao Dong; Carey E. Priebe (IEEE Trans. Inf. Theory, 2020)

Graph Encoder Embedding. - Cencheng Shen; Qizhe Wang; Carey E. Priebe (CoRR, 2021)

The Chi-Square Test of Distance Correlation. - Cencheng Shen; Sambit Panda; Joshua T. Vogelstein (J. Comput. Graph. Stat., 2022)

A Simple Spectral Failure Mode for Graph Convolutional Networks. - Carey E. Priebe; Cencheng Shen; Ningyuan Huang; Tianyi Chen (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Graph Encoder Ensemble for Simultaneous Vertex Embedding and Community Detection. - Cencheng Shen; Youngser Park; Carey E. Priebe (ADMIT, 2023)

Discovering Communication Pattern Shifts in Large-Scale Networks using Encoder Embedding and Vertex Dynamics. - Cencheng Shen; Jonathan Larson; Ha Trinh; Xihan Qin; Youngser Park; Carey E. Priebe (CoRR, 2023)

Learning sources of variability from high-dimensional observational studies. - Eric W. Bridgeford; Jaewon Chung; Brian Gilbert; Sambit Panda; Adam Li; Cencheng Shen; Alexandra Badea; Brian Caffo; Joshua T. Vogelstein (CoRR, 2023)

One-Hot Graph Encoder Embedding. - Cencheng Shen; Qizhe Wang; Carey E. Priebe (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Edge-Parallel Graph Encoder Embedding. - Ariel Lubonja; Cencheng Shen; Carey E. Priebe; Randal C. Burns (IPDPS (Workshops), 2024)

Efficient Graph Encoder Embedding for Large Sparse Graphs in Python. - Xihan Qin; Cencheng Shen (SAI (3), 2024)

Fast and Scalable Multi-Kernel Encoder Classifier. - Cencheng Shen (CoRR, 2024)

Synergistic graph fusion via encoder embedding. - Cencheng Shen; Carey E. Priebe; Jonathan Larson; Ha Trinh (Inf. Sci., 2024)

Discovering the signal subgraph: An iterative screening approach on graphs. - Cencheng Shen; Shangsi Wang; Alexandra Badea; Carey E. Priebe; Joshua T. Vogelstein (Pattern Recognit. Lett., 2024)

Independence Testing for Temporal Data. - Cencheng Shen; Jaewon Chung; Ronak D. Mehta; Ting Xu 001; Joshua T. Vogelstein (Trans. Mach. Learn. Res., 2024)

Discovering Communication Pattern Shifts in Large-Scale Labeled Networks Using Encoder Embedding and Vertex Dynamics. - Cencheng Shen; Jonathan Larson; Ha Trinh; Xihan Qin; Youngser Park; Carey E. Priebe (IEEE Trans. Netw. Sci. Eng., 2024)

Encoder embedding for general graph and node classification. - Cencheng Shen (Appl. Netw. Sci., 2024)

Explaining Categorical Feature Interactions Using Graph Covariance and LLMs. - Cencheng Shen; Darren Edge; Jonathan Larson; Carey E. Priebe (CoRR, 2025)

Principal Graph Encoder Embedding and Principal Community Detection. - Cencheng Shen; Yuexiao Dong; Carey E. Priebe; Jonathan Larson; Ha Trinh; Youngser Park (CoRR, 2025)

A Graph Sufficiency Perspective for Neural Networks. - Cencheng Shen; Yuexiao Dong (CoRR, 2025)

Graph Neural Networks Powered by Encoder Embedding for Improved Node Learning. - Shiyu Chen; Cencheng Shen; Youngser Park; Carey E. Priebe (CoRR, 2025)

Refined graph encoder embedding via self-training and latent community recovery. - Cencheng Shen; Jonathan Larson; Ha Trinh; Carey E. Priebe (Soc. Netw. Anal. Min., 2025)