Data-Driven Analysis and Common Proper Orthogonal Decomposition (CPOD)-Based Spatio-Temporal Emulator for Design Exploration. - Shiang-Ting Yeh; Xingjian Wang; Chih-Li Sung; Simon Mak; Yu-Hung Chang; Liwei Zhang; C. F. Jeff Wu; Vigor Yang (CoRR, 2017)

Kernel-smoothed proper orthogonal decomposition (KSPOD)-based emulation for prediction of spatiotemporally evolving flow dynamics. - Yu-Hung Chang; Liwei Zhang; Xingjian Wang; Shiang-Ting Yeh; Simon Mak; Chih-Li Sung; C. F. Jeff Wu; Vigor Yang (CoRR, 2018)

Maximum Entropy Low-Rank Matrix Recovery. - Simon Mak; Yao Xie 002 (IEEE J. Sel. Top. Signal Process., 2018)

Recent advances on the reduction and analysis of big and high-dimensional data. - Simon Mak (2018)

Distributional Clustering: A distribution-preserving clustering method. - Arvind Krishna; Simon Mak; Roshan Joseph (CoRR, 2019)

Analysis-of-Marginal-Tail-Means (ATM): A Robust Method for Discrete Black-Box Optimization. - Simon Mak; C. F. Jeff Wu (Technometrics, 2019)

Uncertainty Quantification for Inferring Hawkes Networks. - Haoyun Wang; Liyan Xie; Alex Cuozzo; Simon Mak; Yao Xie 002 (NeurIPS, 2020)

TSEC: a framework for online experimentation under experimental constraints. - Simon Mak; Yuanshuo Zhou; Lavonne Hoang; C. F. Jeff Wu (CoRR, 2021)

Sequential change-point detection for mutually exciting point processes over networks. - Haoyun Wang; Liyan Xie; Yao Xie 002; Alex Cuozzo; Simon Mak (CoRR, 2021)

Gaussian Process Subspace Regression for Model Reduction. - Ruda Zhang; Simon Mak; David B. Dunson (CoRR, 2021)

BacHMMachine: An Interpretable and Scalable Model for Algorithmic Harmonization for Four-part Baroque Chorales. - Yunyao Zhu; Stephen Hahn 003; Simon Mak; Yue Jiang; Cynthia Rudin (CoRR, 2021)

Supervised compression of big data. - V. Roshan Joseph; Simon Mak (Stat. Anal. Data Min., 2021)

Function-on-Function Kriging, With Applications to Three-Dimensional Printing of Aortic Tissues. - Jialei Chen 002; Simon Mak; V. Roshan Joseph; Chuck Zhang (Technometrics, 2021)

Gaussian Process Subspace Prediction for Model Reduction. - Ruda Zhang; Simon Mak; David B. Dunson (SIAM J. Sci. Comput., 2022)

TSEC: A Framework for Online Experimentation under Experimental Constraints. - Simon Mak; Yuanshuo Zhao; Lavonne Hoang; C. F. Jeff Wu (Technometrics, 2022)

Population Quasi-Monte Carlo. - Chaofan Huang; V. Roshan Joseph; Simon Mak (J. Comput. Graph. Stat., 2022)

An Interpretable, Flexible, and Interactive Probabilistic Framework for Melody Generation. - Stephen Hahn 003; Rico Zhu; Simon Mak; Cynthia Rudin; Yue Jiang (KDD, 2023)

BayesFLo: Bayesian Fault Localization for Software Testing. - Yi Ji; Ryan Lekivetz; Simon Mak; Joseph Morgan (QRS Companion, 2023)

Additive Multi-Index Gaussian process modeling, with application to multi-physics surrogate modeling of the quark-gluon plasma. - Kevin Li; Simon Mak; Jean-François Paquet; Steffen A. Bass (CoRR, 2023)

Sequential Change-Point Detection for Mutually Exciting Point Processes. - Haoyun Wang; Liyan Xie; Yao Xie 002; Alex Cuozzo; Simon Mak (Technometrics, 2023)

PERCEPT: A New Online Change-Point Detection Method using Topological Data Analysis. - Xiaojun Zheng; Simon Mak; Liyan Xie; Yao Xie 002 (Technometrics, 2023)

Trigonometric Quadrature Fourier Features for Scalable Gaussian Process Regression. - Kevin Li; Max Balakirsky; Simon Mak (AISTATS, 2024)

A New Dataset, Notation Software, and Representation for Computational Schenkerian Analysis. - Stephen Ni-Hahn; Weihan Xu; Zirui Yin; Rico Zhu; Simon Mak; Yue Jiang; Cynthia Rudin (ISMIR, 2024)

SentHYMNent: An Interpretable and Sentiment-Driven Model for Algorithmic Melody Harmonization. - Stephen Hahn 003; Jerry Yin; Rico Zhu; Weihan Xu; Yue Jiang; Simon Mak; Cynthia Rudin (KDD, 2024)

MaLT: Machine-Learning-Guided Test Case Design and Fault Localization of Complex Software Systems. - Yi Ji; Simon Mak; Ryan Lekivetz; Joseph Morgan (MEMOCODE, 2024)

Targeted Variance Reduction: Robust Bayesian Optimization of Black-Box Simulators with Noise Parameters. - John Joshua Miller; Simon Mak (CoRR, 2024)

BayesFLo: Bayesian fault localization of complex software systems. - Yi Ji; Simon Mak; Ryan Lekivetz; Joseph Morgan (CoRR, 2024)

A New Dataset, Notation Software, and Representation for Computational Schenkerian Analysis. - Stephen Ni-Hahn; Weihan Xu; Jerry Yin; Rico Zhu; Simon Mak; Yue Jiang; Cynthia Rudin (CoRR, 2024)

Diverse Expected Improvement (DEI): Diverse Bayesian Optimization of Expensive Computer Simulators. - John Joshua Miller; Simon Mak; Benny Sun; Sai Ranjeet Narayanan; Suo Yang; Zongxuan Sun; Kenneth S. Kim; Chol-Bum M. Kweon (CoRR, 2024)

Local transfer learning Gaussian process modeling, with applications to surrogate modeling of expensive computer simulators. - Xinming Wang; Simon Mak; John Miller; Jianguo Wu (CoRR, 2024)

Conglomerate Multi-fidelity Gaussian Process Modeling, with Application to Heavy-Ion Collisions. - Yi Ji; Henry Shaowu Yuchi; Derek Soeder; Jean-François Paquet; Steffen A. Bass; V. Roshan Joseph; C. F. Jeff Wu; Simon Mak (SIAM/ASA J. Uncertain. Quantification, 2024)

Hierarchical Shrinkage Gaussian Processes: Applications to Computer Code Emulation and Dynamical System Recovery. - Tao Tang; Simon Mak; David B. Dunson (SIAM/ASA J. Uncertain. Quantification, 2024)

Stacking Designs: Designing Multifidelity Computer Experiments with Target Predictive Accuracy. - Chih-Li Sung; Yi (irene) Ji; Simon Mak; Wenjia Wang; Tao Tang (SIAM/ASA J. Uncertain. Quantification, 2024)

eRPCA: Robust Principal Component Analysis for Exponential Family Distributions. - Xiaojun Zheng; Simon Mak; Liyan Xie; Yao Xie 002 (Stat. Anal. Data Min., 2024)

A Graphical Multi-Fidelity Gaussian Process Model, with Application to Emulation of Heavy-Ion Collisions. - Yi Ji; Simon Mak; Derek Soeder; Jean-François Paquet; Steffen A. Bass (Technometrics, 2024)

QuIP: Experimental design for expensive simulators with many Qualitative factors via Integer Programming. - Yen-Chun Liu; Simon Mak (CoRR, 2025)