Simulation-based optimal Bayesian experimental design for nonlinear systems. - Xun Huan; Youssef M. Marzouk (J. Comput. Phys., 2013)

A Greedy Approach for Placement of Subsurface Aquifer Wells in an Ensemble Filtering Framework. - Mohamad E. Gharamti; Youssef M. Marzouk; Xun Huan; Ibrahim Hoteit (DyDESS, 2014)

Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions. - Xun Huan; Cosmin Safta; Khachik Sargsyan; Zachary P. Vane; Guilhem Lacaze; Joseph C. Oefelein; Habib N. Najm (SIAM/ASA J. Uncertain. Quantification, 2018)

Design optimization of a scramjet under uncertainty using probabilistic learning on manifolds. - Roger G. Ghanem; Christian Soize; Cosmin Safta; Xun Huan; Guilhem Lacaze; Joseph C. Oefelein; Habib N. Najm (J. Comput. Phys., 2019)

Entropy-based closure for probabilistic learning on manifolds. - Christian Soize; Roger G. Ghanem; Cosmin Safta; Xun Huan; Zachary P. Vane; Joseph C. Oefelein; Guilhem Lacaze; Habib N. Najm; Qi Tang; X. Chen (J. Comput. Phys., 2019)

Compressive sensing adaptation for polynomial chaos expansions. - Panagiotis Tsilifis; Xun Huan; Cosmin Safta; Khachik Sargsyan; Guilhem Lacaze; Joseph C. Oefelein; Habib N. Najm; Roger G. Ghanem (J. Comput. Phys., 2019)

Identification of the partial differential equations governing microstructure evolution in materials: Inference over incomplete, sparse and spatially non-overlapping data. - Zhenlin Wang; Xun Huan; Krishna C. Garikipati (CoRR, 2020)

Reconstruction of the Density Power Spectrum from Quasar Spectra using Machine Learning. - Maria Han Veiga; Xi Meng; Oleg Y. Gnedin; Nickolay Y. Gnedin; Xun Huan (CoRR, 2021)

Bayesian Sequential Optimal Experimental Design for Nonlinear Models Using Policy Gradient Reinforcement Learning. - Wanggang Shen; Xun Huan (CoRR, 2021)

Automated Loss-of-Balance Event Identification in Older Adults at Risk of Falls during Real-World Walking Using Wearable Inertial Measurement Units. - Jeremiah Hauth; Safa Jabri; Fahad Kamran; Eyoel W. Feleke; Kaleab Nigusie; Lauro V. Ojeda; Shirley Handelzalts; Linda Nyquist; Neil B. Alexander; Xun Huan; Jenna Wiens; Kathleen H. Sienko (Sensors, 2021)

Understanding Uncertainty: How Lay Decision-makers Perceive and Interpret Uncertainty in Human-AI Decision Making. - Snehal Prabhudesai; Leyao Yang; Sumit Asthana; Xun Huan; Q. Vera Liao; Nikola Banovic 001 (IUI, 2023)

Fault Prognosis of Turbofan Engines: Eventual Failure Prediction and Remaining Useful Life Estimation. - Joseph Cohen; Xun Huan; Jun Ni 002 (CoRR, 2023)

Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial. - Venkat Nemani; Luca Biggio; Xun Huan; Zhen Hu; Olga Fink; Anh Tran; Yan Wang; Xiaoping Du; Xiaoge Zhang 001; Chao Hu (CoRR, 2023)

FP-IRL: Fokker-Planck-based Inverse Reinforcement Learning - A Physics-Constrained Approach to Markov Decision Processes. - Chengyang Huang; Siddhartha Srivastava; Xun Huan; Krishna C. Garikipati (CoRR, 2023)

Variational Sequential Optimal Experimental Design using Reinforcement Learning. - Wanggang Shen; Jiayuan Dong; Xun Huan (CoRR, 2023)

Stochastic Deep Koopman Model for Quality Propagation Analysis in Multistage Manufacturing Systems. - Zhiyi Chen; Harshal Maske; Huanyi Shui; Devesh Upadhyay; Michael Hopka; Joseph Cohen; Xingjian Lai; Xun Huan; Jun Ni 002 (CoRR, 2023)

Lowering the computational barrier: Partially Bayesian neural networks for transparency in medical imaging AI. - Snehal Prabhudesai; Jeremiah Hauth; Dingkun Guo; Arvind Rao; Nikola Banovic 001; Xun Huan (Frontiers Comput. Sci., 2023)

A Bayesian Approach for Quantifying Data Scarcity when Modeling Human Behavior via Inverse Reinforcement Learning. - Tahera Hossain; Wanggang Shen; Anindya Das Antar; Snehal Prabhudesai; Sozo Inoue; Xun Huan; Nikola Banovic 001 (ACM Trans. Comput. Hum. Interact., 2023)

Deep Koopman-Based Control of Quality Variation in Multistage Manufacturing Systems. - Zhiyi Chen; Harshal Maske; Devesh Upadhyay; Huanyi Shui; Xun Huan; Jun Ni 002 (ACC, 2024)

Exploring Random Forest Machine Learning for Fetal Movement Detection using Abdominal Acceleration and Angular Rate Data. - Lucy Spicher; Carrie Bell; Xun Huan; Kathleen H. Sienko (EMBC, 2024)

Optimal experimental design: Formulations and computations. - Xun Huan; Jayanth Jagalur; Youssef M. Marzouk (Acta Numer., 2024)

Enhancing Dynamical System Modeling through Interpretable Machine Learning Augmentations: A Case Study in Cathodic Electrophoretic Deposition. - Christian Jacobsen; Jiayuan Dong; Mehdi Khalloufi; Xun Huan; Karthik Duraisamy; Maryam Akram; Wanjiao Liu (CoRR, 2024)

Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes. - Jeremiah Hauth; Cosmin Safta; Xun Huan; Ravi G. Patel; Reese E. Jones (CoRR, 2024)

Goal-Oriented Bayesian Optimal Experimental Design for Nonlinear Models using Markov Chain Monte Carlo. - Shijie Zhong; Wanggang Shen; Tommie A. Catanach; Xun Huan (CoRR, 2024)

Variational Bayesian Optimal Experimental Design with Normalizing Flows. - Jiayuan Dong; Christian Jacobsen; Mehdi Khalloufi; Maryam Akram; Wanjiao Liu; Karthik Duraisamy; Xun Huan (CoRR, 2024)

Shapley-based explainable AI for clustering applications in fault diagnosis and prognosis. - Joseph Cohen; Xun Huan; Jun Ni 002 (J. Intell. Manuf., 2024)

Goal-Oriented Sequential Bayesian Experimental Design for Causal Learning. - R. Z. Zhang; Jiayuan Dong; Jie Liu; Xun Huan (CoRR, 2025)