Simon Mak - RankMe

46 papers A* 4A 1B 1C 1Journal 36Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	AutoSchA: Automatic Hierarchical Music Representations via Multi-Relational Node Isolation. AAAI Stephen Ni-Hahn, Rico Zhu, Jerry Yin, Yue Jiang, Cynthia Rudin, Simon Mak
2026	J	`jnl`	Local Transfer Learning Gaussian Process Modeling, with Applications to Surrogate Modeling of Expensive Computer Simulators. SIAM/ASA J. Uncertain. Quantification Xinming Wang, Simon Mak, John Miller, Jianguo Wu
2025	J	`jnl`	AutoSchA: Automatic Hierarchical Music Representations via Multi-Relational Node Isolation. CoRR Stephen Ni-Hahn, Rico Zhu, Jerry Yin, Yue Jiang, Cynthia Rudin, Simon Mak
2025	J	`jnl`	ProGress: Structured Music Generation via Graph Diffusion and Hierarchical Music Analysis. CoRR Stephen Ni-Hahn, Chao Péter Yang, Mingchen Ma, Cynthia Rudin, Simon Mak, Yue Jiang
2025	J	`jnl`	ProSpar-GP: Scalable Gaussian Process Modeling with Massive Nonstationary Datasets. J. Comput. Graph. Stat. Kevin Li, Simon Mak
2025	J	`jnl`	QuIP: Experimental design for expensive simulators with many Qualitative factors via Integer Programming. CoRR Yen-Chun Liu, Simon Mak
2025	J	`jnl`	Targeted Variance Reduction: Effective Bayesian Optimization of Black-Box Simulators with Noise Parameters. Technometrics John Joshua Miller, Simon Mak
2024	J	`jnl`	A Graphical Multi-Fidelity Gaussian Process Model, with Application to Emulation of Heavy-Ion Collisions. Technometrics Yi Ji, Simon Mak, Derek Soeder, Jean-François Paquet, Steffen A. Bass
2024	—	`conf`	A New Dataset, Notation Software, and Representation for Computational Schenkerian Analysis. ISMIR Stephen Ni-Hahn, Weihan Xu, Zirui Yin, Rico Zhu, Simon Mak, Yue Jiang, Cynthia Rudin
2024	J	`jnl`	A New Dataset, Notation Software, and Representation for Computational Schenkerian Analysis. CoRR Stephen Ni-Hahn, Weihan Xu, Jerry Yin, Rico Zhu, Simon Mak, Yue Jiang, Cynthia Rudin
2024	J	`jnl`	BayesFLo: Bayesian fault localization of complex software systems. CoRR Yi Ji, Simon Mak, Ryan Lekivetz, Joseph Morgan
2024	J	`jnl`	Conglomerate Multi-fidelity Gaussian Process Modeling, with Application to Heavy-Ion Collisions. SIAM/ASA J. Uncertain. Quantification Yi Ji, Henry Shaowu Yuchi, Derek Soeder, Jean-François Paquet, Steffen A. Bass, V. Roshan Joseph, C. F. Jeff Wu, Simon Mak
2024	J	`jnl`	Diverse Expected Improvement (DEI): Diverse Bayesian Optimization of Expensive Computer Simulators. CoRR John Joshua Miller, Simon Mak, Benny Sun, Sai Ranjeet Narayanan, Suo Yang, Zongxuan Sun, Kenneth S. Kim, Chol-Bum M. Kweon
2024	J	`jnl`	Hierarchical Shrinkage Gaussian Processes: Applications to Computer Code Emulation and Dynamical System Recovery. SIAM/ASA J. Uncertain. Quantification Tao Tang, Simon Mak, David B. Dunson
2024	J	`jnl`	Local transfer learning Gaussian process modeling, with applications to surrogate modeling of expensive computer simulators. CoRR Xinming Wang, Simon Mak, John Miller, Jianguo Wu
2024	C	`conf`	MaLT: Machine-Learning-Guided Test Case Design and Fault Localization of Complex Software Systems. MEMOCODE Yi Ji, Simon Mak, Ryan Lekivetz, Joseph Morgan
2024	A*	`conf`	SentHYMNent: An Interpretable and Sentiment-Driven Model for Algorithmic Melody Harmonization. KDD Stephen Hahn, Jerry Yin, Rico Zhu, Weihan Xu, Yue Jiang, Simon Mak, Cynthia Rudin
2024	J	`jnl`	Stacking Designs: Designing Multifidelity Computer Experiments with Target Predictive Accuracy. SIAM/ASA J. Uncertain. Quantification Chih-Li Sung, Yi (irene) Ji, Simon Mak, Wenjia Wang, Tao Tang
2024	J	`jnl`	Targeted Variance Reduction: Robust Bayesian Optimization of Black-Box Simulators with Noise Parameters. CoRR John Joshua Miller, Simon Mak
2024	A	`conf`	Trigonometric Quadrature Fourier Features for Scalable Gaussian Process Regression. AISTATS Kevin Li, Max Balakirsky, Simon Mak
2023	J	`jnl`	Additive Multi-Index Gaussian process modeling, with application to multi-physics surrogate modeling of the quark-gluon plasma. CoRR Kevin Li, Simon Mak, Jean-François Paquet, Steffen A. Bass
2023	A*	`conf`	An Interpretable, Flexible, and Interactive Probabilistic Framework for Melody Generation. KDD Stephen Hahn, Rico Zhu, Simon Mak, Cynthia Rudin, Yue Jiang
2023	—	`conf`	BayesFLo: Bayesian Fault Localization for Software Testing. QRS Companion Yi Ji, Ryan Lekivetz, Simon Mak, Joseph Morgan
2023	J	`jnl`	Hierarchical shrinkage Gaussian processes: applications to computer code emulation and dynamical system recovery. CoRR Tao Tang, Simon Mak, David B. Dunson
2023	J	`jnl`	PERCEPT: A New Online Change-Point Detection Method using Topological Data Analysis. Technometrics Xiaojun Zheng, Simon Mak, Liyan Xie, Yao Xie
2023	J	`jnl`	Sequential Change-Point Detection for Mutually Exciting Point Processes. Technometrics Haoyun Wang, Liyan Xie, Yao Xie, Alex Cuozzo, Simon Mak
2023	J	`jnl`	Trigonometric Quadrature Fourier Features for Scalable Gaussian Process Regression. CoRR Kevin Li, Max Balakirsky, Simon Mak
2022	J	`jnl`	Gaussian Process Subspace Prediction for Model Reduction. SIAM J. Sci. Comput. Ruda Zhang, Simon Mak, David B. Dunson
2022	J	`jnl`	Population Quasi-Monte Carlo. J. Comput. Graph. Stat. Chaofan Huang, V. Roshan Joseph, Simon Mak
2022	J	`jnl`	TSEC: A Framework for Online Experimentation under Experimental Constraints. Technometrics Simon Mak, Yuanshuo Zhao, Lavonne Hoang, C. F. Jeff Wu
2021	J	`jnl`	BacHMMachine: An Interpretable and Scalable Model for Algorithmic Harmonization for Four-part Baroque Chorales. CoRR Yunyao Zhu, Stephen Hahn, Simon Mak, Yue Jiang, Cynthia Rudin
2021	J	`jnl`	Function-on-Function Kriging, With Applications to Three-Dimensional Printing of Aortic Tissues. Technometrics Jialei Chen, Simon Mak, V. Roshan Joseph, Chuck Zhang
2021	J	`jnl`	Gaussian Process Subspace Regression for Model Reduction. CoRR Ruda Zhang, Simon Mak, David B. Dunson
2021	J	`jnl`	Sequential change-point detection for mutually exciting point processes over networks. CoRR Haoyun Wang, Liyan Xie, Yao Xie, Alex Cuozzo, Simon Mak
2021	J	`jnl`	Supervised compression of big data. Stat. Anal. Data Min. V. Roshan Joseph, Simon Mak
2021	J	`jnl`	TSEC: a framework for online experimentation under experimental constraints. CoRR Simon Mak, Yuanshuo Zhou, Lavonne Hoang, C. F. Jeff Wu
2020	A*	`conf`	Uncertainty Quantification for Inferring Hawkes Networks. NeurIPS Haoyun Wang, Liyan Xie, Alex Cuozzo, Simon Mak, Yao Xie
2020	J	`jnl`	Uncertainty Quantification for Inferring Hawkes Networks. CoRR Haoyun Wang, Liyan Xie, Alex Cuozzo, Simon Mak, Yao Xie
2019	J	`jnl`	Analysis-of-Marginal-Tail-Means (ATM): A Robust Method for Discrete Black-Box Optimization. Technometrics Simon Mak, C. F. Jeff Wu
2019	J	`jnl`	Distributional Clustering: A distribution-preserving clustering method. CoRR Arvind Krishna, Simon Mak, Roshan Joseph
2018	J	`jnl`	Kernel-smoothed proper orthogonal decomposition (KSPOD)-based emulation for prediction of spatiotemporally evolving flow dynamics. CoRR Yu-Hung Chang, Liwei Zhang, Xingjian Wang, Shiang-Ting Yeh, Simon Mak, Chih-Li Sung, C. F. Jeff Wu, Vigor Yang
2018	B	`conf`	Maximum Entropy Low-Rank Matrix Recovery. ISIT Simon Mak, Yao Xie
2018	J	`jnl`	Maximum Entropy Low-Rank Matrix Recovery. IEEE J. Sel. Top. Signal Process. Simon Mak, Yao Xie
2018	—	`—`	Recent advances on the reduction and analysis of big and high-dimensional data. Simon Mak
2017	J	`jnl`	Data-Driven Analysis and Common Proper Orthogonal Decomposition (CPOD)-Based Spatio-Temporal Emulator for Design Exploration. CoRR Shiang-Ting Yeh, Xingjian Wang, Chih-Li Sung, Simon Mak, Yu-Hung Chang, Liwei Zhang, C. F. Jeff Wu, Vigor Yang
2017	J	`jnl`	Maximum entropy low-rank matrix recovery. CoRR Simon Mak, Yao Xie