Liping Wang

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A Robust and Efficient Probabilistic Approach for Challenging Industrial Applications with High -dimensional and Non -monotonic Design Spaces

Liping Wang, Don Beeson, Neumann Way, 2006 .

Data-based Discovery of Governing Equations pdf

Piyush Pandita, Liping Wang, Sayan Ghosh, 2020, AAAI Spring Symposium: MLPS.

Data-Informed Decomposition for Localized Uncertainty Quantification of Dynamical Systems

Piyush Pandita, Sayan Ghosh, W. Subber, 2020, Vibration.

Efficient Moment and Probability Distribution Estimation Using the Point Estimate Method for High- dimensional Engineering Problems

Liping Wang, Don Beeson, Gene Wiggs, 2007 .

Multifidelity Model Calibration in Structural Dynamics Using Stochastic Variational Inference on Manifolds

Piyush Pandita, P. Tsilifis, Sayan Ghosh, 2022, Entropy.

Data-driven discovery of free-form governing differential equations

R. Ghanem, Genghis Khan, W. Subber, 2019, ArXiv.

Dynamic Bayesian Network for Aircraft Wing Health Monitoring Digital Twin

Sankaran Mahadevan, Liping Wang, You Ling, 2017 .

Advances in Bayesian Probabilistic Modeling for Industrial Applications pdf

Yiming Zhang, Liping Wang, Piyush Pandita, 2020, ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg.

Efficient robust design optimization using Gaussian process and intelligent sampling

Kevin Ryan, Jesper Kristensen, You Ling, 2018, 2018 Multidisciplinary Analysis and Optimization Conference.

An intelligent sampling framework for multi-objective optimization in high dimensional design space

Kevin Ryan, Jesper Kristensen, You Ling, 2018 .

A Strategy for Adaptive Sampling of Multi-fidelity Gaussian Process to Reduce Predictive Uncertainty pdf

Liping Wang, Yiming Zhang, Sayan Ghosh, 2019, Volume 2B: 45th Design Automation Conference.

Computationally Efficient Bayesian Optimization for Multi-objective Industrial Applications

Liping Wang, Piyush Pandita, Sayan Ghosh, 2020, AIAA Scitech 2021 Forum.

Towards Scalable Gaussian Process Modeling pdf

Piyush Pandita, Liping Wang, Jesper Kristensen, 2019, Volume 2B: 45th Design Automation Conference.

Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes pdf

Liping Wang, Piyush Pandita, Sayan Ghosh, 2020, Computer Methods in Applied Mechanics and Engineering.

Challenges in Uncertainty, Calibration, Validation and Predictability of Engineering Analysis Models

Liping Wang, John Nelson, Gene Wiggs, 2011 .

Hybrid Bayesian Solution to NASA Langley Research Center Multidisciplinary Uncertainty Quantification Challenge

Ankur Srivastava, Liping Wang, Arun K. Subramaniyan, 2015, J. Aerosp. Inf. Syst..

A Comparison Of Meta -modeling Methods Using Practical Industry Requirements

Liping Wang, Mahidhar Rayasam, Gene Wiggs, 2006 .

Pro-ML IDeAS: A Probabilistic Framework for Explicit Inverse Design using Invertible Neural Network

Liping Wang, Piyush Pandita, Genghis Khan, 2020, AIAA Scitech 2021 Forum.

Discovery of Physics and Characterization of Microstructure from Data with Bayesian Hidden Physics Models pdf

Liping Wang, Steven Atkinson, Yiming Zhang, 2021, AAAI Spring Symposium: MLPS.

Probabilistic Validation Metrics for Industrial Engineering Analysis Models

Liping Wang, Gulshan Singh, Arun K. Subramaniyan, 2012 .

Scalable Fully Bayesian Gaussian Process Modeling and Calibration With Adaptive Sequential Monte Carlo for Industrial Applications

Liping Wang, Piyush Pandita, Panagiotis Tsilifis, 2021 .

Analytical global sensitivity analysis with Gaussian processes

Ankur Srivastava, Liping Wang, Arun K. Subramaniyan, 2017, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

A dynamic Bayesian network approach for digital twin

Sankaran Mahadevan, You Ling, Chenzhao Li, 2017 .

Industrial Applications of Intelligent Adaptive Sampling Methods for Multi-Objective Optimization

Liping Wang, Yiming Zhang, Sayan Ghosh, 2019, Design and Manufacturing.

Inverse Aerodynamic Design of Gas Turbine Blades using Probabilistic Machine Learning pdf

Liping Wang, Piyush Pandita, Nicholas Zabaras, 2021, Journal of Mechanical Design.

Learning Uncertainty using Clustering and Local Gaussian Process Regression

Yiming Zhang, You Ling, Sayan Ghosh, 2019, AIAA Scitech 2019 Forum.

Bayesian task embedding for few-shot Bayesian optimization pdf

Liping Wang, Sayan Ghosh, Genghis Khan, 2020, AIAA Scitech 2020 Forum.

Information gain-based inspection scheduling for fatigued aircraft components

You Ling, Isaac Asher, Liping Wang, 2017 .

Application of probabilistic modeling and automated machine learning framework for high-dimensional stress field

M. Anitescu, Piyush Pandita, Changjie Sun, 2023, arXiv.org.

Remarks for Scaling Up a General Gaussian Process to Model Large Dataset with Sub-models

Liping Wang, Piyush Pandita, Yiming Zhang, 2020 .

Gaussian Process Meta-Models for Efficient Probabilistic Design in Complex Engineering Design Spaces

Liping Wang, Gene Wiggs, Don Beeson, 2005, DAC 2005.

Application of Deep Transfer Learning and Uncertainty Quantification for Process Identification in Powder Bed Fusion

Piyush Pandita, Andrey Meshkov, V. Gupta, 2021, ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg.

On Uncertainty Quantification in Materials Modeling and Discovery: Applications of GE's BHM and IDACE

V. Dheeradhada, Changjie Sun, A. Kitt, 2023, AIAA SCITECH 2023 Forum.

Expected-Improvement-Based Methods for Adaptive Sampling in Multi-Objective Optimization Problems

Liping Wang, Jesper Kristensen, You Ling, 2016, DAC 2016.

Calibrating Transient Models With Multiple Responses Using Bayesian Inverse Techniques

Liping Wang, Gene Wiggs, Arun K. Subramaniyan, 2013 .

Improving High-Dimensional Physics Models Through Bayesian Calibration With Uncertain Data

Liping Wang, Arun K. Subramaniyan, Natarajan Chennimalai Kumar, 2012 .