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Xun Huan
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2020 – today
- 2024
- [j9]Xun Huan, Jayanth Jagalur, Youssef M. Marzouk
:
Optimal experimental design: Formulations and computations. Acta Numer. 33: 715-840 (2024) - [c3]Zhiyi Chen, Harshal Maske, Devesh Upadhyay, Huanyi Shui, Xun Huan, Jun Ni:
Deep Koopman-Based Control of Quality Variation in Multistage Manufacturing Systems. ACC 2024: 893-898 - [i16]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 abs/2401.08414 (2024) - [i15]Jeremiah Hauth, Cosmin Safta, Xun Huan, Ravi G. Patel, Reese E. Jones:
Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes. CoRR abs/2402.11179 (2024) - [i14]Shijie Zhong, Wanggang Shen, Tommie A. Catanach, Xun Huan:
Goal-Oriented Bayesian Optimal Experimental Design for Nonlinear Models using Markov Chain Monte Carlo. CoRR abs/2403.18072 (2024) - [i13]Jiayuan Dong, Christian Jacobsen, Mehdi Khalloufi, Maryam Akram, Wanjiao Liu, Karthik Duraisamy, Xun Huan:
Variational Bayesian Optimal Experimental Design with Normalizing Flows. CoRR abs/2404.13056 (2024) - [i12]Xun Huan, Jayanth Jagalur, Youssef M. Marzouk:
Optimal experimental design: Formulations and computations. CoRR abs/2407.16212 (2024) - [i11]Zhiyi Chen, Harshal Maske, Devesh Upadhyay, Huanyi Shui, Xun Huan, Jun Ni:
Deep Koopman-based Control of Quality Variation in Multistage Manufacturing Systems. CoRR abs/2407.16933 (2024) - 2023
- [j8]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) - [j7]Tahera Hossain
A Bayesian Approach for Quantifying Data Scarcity when Modeling Human Behavior via Inverse Reinforcement Learning. ACM Trans. Comput. Hum. Interact. 30(1): 1-27 (2023) - [c2]Snehal Prabhudesai
Understanding Uncertainty: How Lay Decision-makers Perceive and Interpret Uncertainty in Human-AI Decision Making. IUI 2023: 379-396 - [i10]Joseph Cohen, Xun Huan, Jun Ni:
Fault Prognosis of Turbofan Engines: Eventual Failure Prediction and Remaining Useful Life Estimation. CoRR abs/2303.12982 (2023) - [i9]Joseph Cohen, Xun Huan, Jun Ni:
Shapley-based Explainable AI for Clustering Applications in Fault Diagnosis and Prognosis. CoRR abs/2303.14581 (2023) - [i8]Venkat Nemani, Luca Biggio, Xun Huan, Zhen Hu, Olga Fink
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial. CoRR abs/2305.04933 (2023) - [i7]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 abs/2306.10407 (2023) - [i6]Wanggang Shen, Jiayuan Dong, Xun Huan:
Variational Sequential Optimal Experimental Design using Reinforcement Learning. CoRR abs/2306.10430 (2023) - [i5]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 abs/2309.10193 (2023) - 2021
- [j6]Jeremiah Hauth
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): 4661 (2021) - [i4]Maria Han Veiga, Xi Meng, Oleg Y. Gnedin
Reconstruction of the Density Power Spectrum from Quasar Spectra using Machine Learning. CoRR abs/2107.09082 (2021) - [i3]Wanggang Shen, Xun Huan:
Bayesian Sequential Optimal Experimental Design for Nonlinear Models Using Policy Gradient Reinforcement Learning. CoRR abs/2110.15335 (2021) - 2020
- [i2]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 abs/2001.04816 (2020)
2010 – 2019
- 2019
- [j5]Panagiotis Tsilifis
Compressive sensing adaptation for polynomial chaos expansions. J. Comput. Phys. 380: 29-47 (2019) - [j4]Christian Soize
Entropy-based closure for probabilistic learning on manifolds. J. Comput. Phys. 388: 518-533 (2019) - [j3]Roger G. Ghanem
Design optimization of a scramjet under uncertainty using probabilistic learning on manifolds. J. Comput. Phys. 399 (2019) - 2018
- [j2]Xun Huan
Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions. SIAM/ASA J. Uncertain. Quantification 6(2): 907-936 (2018) - 2017
- [i1]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 abs/1707.09334 (2017) - 2014
- [c1]Mohamad E. Gharamti, Youssef M. Marzouk, Xun Huan
A Greedy Approach for Placement of Subsurface Aquifer Wells in an Ensemble Filtering Framework. DyDESS 2014: 301-309 - 2013
- [j1]Xun Huan
Simulation-based optimal Bayesian experimental design for nonlinear systems. J. Comput. Phys. 232(1): 288-317 (2013)
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