Guang Lin

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Citations	6119	4270
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George Em KarniadakisThe Charles Pitts Robinson and John Palmer Barstow Professor of Applied Mathematics and EngineeringVerified email at brown.edu
Bledar Alexandros KonomiAssociate Professor, Department of Mathematical Sciences, University of CincinnatiVerified email at uc.edu
Faming LiangDistinguished Professor of Statistics, Purdue UniversityVerified email at purdue.edu
Zhangshuan (Jason) HouPacific Northwest National LaboratoryVerified email at pnnl.gov
Ben YangSchool of Atmospheric Sciences, Nanjing UniversityVerified email at nju.edu.cn
Alexandre TartakovskyUniversity of Illinois Urbana-Champaign and Pacific Northwest National LaboratoryVerified email at pnnl.gov
Weixuan LiMicrosoftVerified email at microsoft.com
Yun QianPNNLVerified email at pnnl.gov
Bin ZhengScientist, Pacific Northwest National LaboratoryVerified email at pnnl.gov
Shuai LuFounder and CEO, EnerModVerified email at enermod.com
Ning ZhouAssociate Professor, SUNY Binghamton UniversityVerified email at binghamton.edu
Jie BaoResearch Engineer, Experimental and Computational Engineering Group, Pacific Northwest NationalVerified email at pnnl.gov
Chun ZhaoUniversity of Science and Technology of ChinaVerified email at ustc.edu.cn
Shaobu WangPacific Northwest National LabVerified email at pnnl.gov
Xiaoliang WanLouisiana State UniversityVerified email at math.lsu.edu
J. Nathan KutzProfessor of Applied Mathematics & Electrical and Computer EngineeringVerified email at uw.edu
Xiaohong LiuReta Haynes Chair in Geosciences, Professor of Atmospheric Sciences, Texas A&M UniversityVerified email at tamu.edu
Hailong WangPacific Northwest National LaboratoryVerified email at pnnl.gov
Minghuai WangSchool of Atmospheric Sciences, Nanjing UniversityVerified email at nju.edu.cn
Marcelo A ElizondoPacific Northwest National LaboratoryVerified email at pnnl.gov

Guang Lin

Associate Dean for Research, Professor of Mathematics, Mech Eng, Statistics, Purdue University

Verified email at purdue.edu - Homepage

Scientific Machine Learning Uncertainty Quantification Generative AI LLM Deep Learning


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Multi-output separable Gaussian process: Towards an efficient, fully Bayesian paradigm for uncertainty quantification I Bilionis, N Zabaras, BA Konomi, G Lin Journal of Computational Physics 241, 212-239, 2013	204	2013
Robust data-driven discovery of governing physical laws with error bars S Zhang, G Lin Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2018	197	2018
Compressive sensing based machine learning strategy for characterizing the flow around a cylinder with limited pressure measurements I Bright, G Lin, JN Kutz Physics of Fluids 25 (12), 2013	176	2013
Adaptive ANOVA decomposition of stochastic incompressible and compressible flows X Yang, M Choi, G Lin, GE Karniadakis Journal of Computational Physics 231 (4), 1587-1614, 2012	158	2012
Some issues in uncertainty quantification and parameter tuning: A case study of convective parameterization scheme in the WRF regional climate model B Yang, Y Qian, G Lin, R Leung, Y Zhang Atmospheric Chemistry and Physics 12 (5), 2409-2427, 2012	149	2012
An efficient, high-order probabilistic collocation method on sparse grids for three-dimensional flow and solute transport in randomly heterogeneous porous media G Lin, AM Tartakovsky Advances in Water Resources 32 (5), 712-722, 2009	140	2009
Uncertainty quantification and parameter tuning in the CAM5 Zhang‐McFarlane convection scheme and impact of improved convection on the global circulation and climate B Yang, Y Qian, G Lin, LR Leung, PJ Rasch, GJ Zhang, SA McFarlane, ... Journal of Geophysical Research: Atmospheres 118 (2), 395-415, 2013	128	2013
Sensitivity of surface flux simulations to hydrologic parameters based on an uncertainty quantification framework applied to the Community Land Model Z Hou, M Huang, LR Leung, G Lin, DM Ricciuto Journal of Geophysical Research: Atmospheres 117 (D15), 2012	125	2012
Multi-resolution climate ensemble parameter analysis with nested parallel coordinates plots J Wang, X Liu, HW Shen, G Lin IEEE transactions on visualization and computer graphics 23 (1), 81-90, 2016	122	2016
ConvPDE-UQ: Convolutional neural networks with quantified uncertainty for heterogeneous elliptic partial differential equations on varied domains N Winovich, K Ramani, G Lin Journal of Computational Physics 394, 263-279, 2019	116	2019
Generating random earthquake events for probabilistic tsunami hazard assessment RJ LeVeque, K Waagan, FI González, D Rim, G Lin Global Tsunami Science: Past and Future, Volume I, 3671-3692, 2017	103	2017
Deeplight: Deep lightweight feature interactions for accelerating ctr predictions in ad serving W Deng, J Pan, T Zhou, D Kong, A Flores, G Lin Proceedings of the 14th ACM international conference on Web search and data …, 2021	91	2021
Predicting shock dynamics in the presence of uncertainties G Lin, CH Su, GE Karniadakis Journal of Computational Physics 217 (1), 260-276, 2006	83	2006
An iterative local updating ensemble smoother for estimation and uncertainty assessment of hydrologic model parameters with multimodal distributions J Zhang, G Lin, W Li, L Wu, L Zeng Water Resources Research 54 (3), 1716-1733, 2018	76	2018
Weak Galerkin finite element methods for Darcy flow: Anisotropy and heterogeneity G Lin, J Liu, L Mu, X Ye Journal of computational physics 276, 422-437, 2014	76	2014
Dynamic-feature extraction, attribution, and reconstruction (DEAR) method for power system model reduction S Wang, S Lu, N Zhou, G Lin, M Elizondo, MA Pai IEEE transactions on power systems 29 (5), 2049-2059, 2014	75	2014
Identifiability and predictability of integer-and fractional-order epidemiological models using physics-informed neural networks E Kharazmi, M Cai, X Zheng, Z Zhang, G Lin, GE Karniadakis Nature Computational Science 1 (11), 744-753, 2021	73	2021
A Comparative Study of YH Tang, G Lin, H Sun	72	2021
Uncertainty quantification via random domain decomposition and probabilistic collocation on sparse grids G Lin, AM Tartakovsky, DM Tartakovsky Journal of Computational Physics 229 (19), 6995-7012, 2010	72	2010
A sensitivity study of radiative fluxes at the top of atmosphere to cloud-microphysics and aerosol parameters in the community atmosphere model CAM5 C Zhao, X Liu, Y Qian, J Yoon, Z Hou, G Lin, S McFarlane, H Wang, ... Atmospheric Chemistry and Physics 13 (21), 10969-10987, 2013	67	2013

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