Xun Huan

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 24

Top Topics

Markov Decision Process

Experimental Design

Compressive Sensing

Top Venues

J. Comput. Phys.

SIAM/ASA J. Uncertain. Quantification

Publications

Xun Huan, Jayanth Jagalur, Youssef M. Marzouk
Optimal experimental design: Formulations and computations. CoRR (2024)
Christian Jacobsen, Jiayuan Dong, Mehdi Khalloufi, Xun Huan, Karthik Duraisamy, Maryam Akram, Wanjiao Liu
Enhancing Dynamical System Modeling through Interpretable Machine Learning Augmentations: A Case Study in Cathodic Electrophoretic Deposition. CoRR (2024)
Jeremiah Hauth, Cosmin Safta, Xun Huan, Ravi G. Patel, Reese E. Jones
Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes. CoRR (2024)
Shijie Zhong, Wanggang Shen, Tommie A. Catanach, Xun Huan
Goal-Oriented Bayesian Optimal Experimental Design for Nonlinear Models using Markov Chain Monte Carlo. CoRR (2024)
Jiayuan Dong, Christian Jacobsen, Mehdi Khalloufi, Maryam Akram, Wanjiao Liu, Karthik Duraisamy, Xun Huan
Variational Bayesian Optimal Experimental Design with Normalizing Flows. CoRR (2024)
Zhiyi Chen, Harshal Maske, Devesh Upadhyay, Huanyi Shui, Xun Huan, Jun Ni
Deep Koopman-based Control of Quality Variation in Multistage Manufacturing Systems. CoRR (2024)
Snehal Prabhudesai, Leyao Yang, Sumit Asthana, Xun Huan, Q. Vera Liao, Nikola Banovic
Understanding Uncertainty: How Lay Decision-makers Perceive and Interpret Uncertainty in Human-AI Decision Making. IUI (2023)
Chengyang Huang, Siddhartha Srivastava, Xun Huan, Krishna C. Garikipati
FP-IRL: Fokker-Planck-based Inverse Reinforcement Learning - A Physics-Constrained Approach to Markov Decision Processes. CoRR (2023)
Venkat Nemani, Luca Biggio, Xun Huan, Zhen Hu, Olga Fink, Anh Tran, Yan Wang, Xiaoping Du, Xiaoge Zhang, Chao Hu
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial. CoRR (2023)
Wanggang Shen, Jiayuan Dong, Xun Huan
Variational Sequential Optimal Experimental Design using Reinforcement Learning. CoRR (2023)
Joseph Cohen, Xun Huan, Jun Ni
Fault Prognosis of Turbofan Engines: Eventual Failure Prediction and Remaining Useful Life Estimation. CoRR (2023)
Joseph Cohen, Xun Huan, Jun Ni
Shapley-based Explainable AI for Clustering Applications in Fault Diagnosis and Prognosis. CoRR (2023)
Tahera Hossain, Wanggang Shen, Anindya Das Antar, Snehal Prabhudesai, Sozo Inoue, Xun Huan, Nikola Banovic
A Bayesian Approach for Quantifying Data Scarcity when Modeling Human Behavior via Inverse Reinforcement Learning. ACM Trans. Comput. Hum. Interact. 30 (1) (2023)
Snehal Prabhudesai, Jeremiah Hauth, Dingkun Guo, Arvind Rao, Nikola Banovic, Xun Huan
Lowering the computational barrier: Partially Bayesian neural networks for transparency in medical imaging AI. Frontiers Comput. Sci. 5 (2023)
Zhiyi Chen, Harshal Maske, Huanyi Shui, Devesh Upadhyay, Michael Hopka, Joseph Cohen, Xingjian Lai, Xun Huan, Jun Ni
Stochastic Deep Koopman Model for Quality Propagation Analysis in Multistage Manufacturing Systems. CoRR (2023)
Jeremiah Hauth, Safa Jabri, Fahad Kamran, Eyoel W. Feleke, Kaleab Nigusie, Lauro Ojeda, Shirley Handelzalts, Linda Nyquist, Neil B. Alexander, Xun Huan, Jenna Wiens, Kathleen H. Sienko
Automated Loss-of-Balance Event Identification in Older Adults at Risk of Falls during Real-World Walking Using Wearable Inertial Measurement Units. Sensors 21 (14) (2021)
Wanggang Shen, Xun Huan
Bayesian Sequential Optimal Experimental Design for Nonlinear Models Using Policy Gradient Reinforcement Learning. CoRR (2021)
Maria Han Veiga, Xi Meng, Oleg Y. Gnedin, Nickolay Y. Gnedin, Xun Huan
Reconstruction of the Density Power Spectrum from Quasar Spectra using Machine Learning. CoRR (2021)
Zhenlin Wang, Xun Huan, Krishna C. Garikipati
Identification of the partial differential equations governing microstructure evolution in materials: Inference over incomplete, sparse and spatially non-overlapping data. CoRR (2020)
Panagiotis Tsilifis, Xun Huan, Cosmin Safta, Khachik Sargsyan, Guilhem Lacaze, Joseph C. Oefelein, Habib N. Najm, Roger G. Ghanem
Compressive sensing adaptation for polynomial chaos expansions. J. Comput. Phys. 380 (2019)
Christian Soize, Roger G. Ghanem, Cosmin Safta, Xun Huan, Zachary P. Vane, Joseph C. Oefelein, Guilhem Lacaze, Habib N. Najm, Q. Tang, X. Chen
Entropy-based closure for probabilistic learning on manifolds. J. Comput. Phys. 388 (2019)
Roger G. Ghanem, Christian Soize, Cosmin Safta, Xun Huan, Guilhem Lacaze, Joseph C. Oefelein, Habib N. Najm
Design optimization of a scramjet under uncertainty using probabilistic learning on manifolds. J. Comput. Phys. 399 (2019)
Xun Huan, Cosmin Safta, Khachik Sargsyan, Zachary P. Vane, Guilhem Lacaze, Joseph C. Oefelein, Habib N. Najm
Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions. SIAM/ASA J. Uncertain. Quantification 6 (2) (2018)
Xun Huan, Cosmin Safta, Khachik Sargsyan, Zachary P. Vane, Guilhem Lacaze, Joseph C. Oefelein, Habib N. Najm
Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions. CoRR (2017)
Mohamad E. Gharamti, Youssef M. Marzouk, Xun Huan, Ibrahim Hoteit
A Greedy Approach for Placement of Subsurface Aquifer Wells in an Ensemble Filtering Framework. DyDESS (2014)
Xun Huan, Youssef M. Marzouk
Simulation-based optimal Bayesian experimental design for nonlinear systems. J. Comput. Phys. 232 (1) (2013)