Guang Lin

Dikutip oleh

	Semua	Sejak 2020
Kutipan	6630	4448
indeks-h	43	35
indeks-i10	160	125

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157 artikel

12 artikel

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George Em KarniadakisThe Charles Pitts Robinson and John Palmer Barstow Professor of Applied Mathematics and EngineeringEmail yang diverifikasi di brown.edu
Bledar Alexandros KonomiAssociate Professor, Department of Mathematical Sciences, University of CincinnatiEmail yang diverifikasi di uc.edu
Faming LiangDistinguished Professor of Statistics, Purdue UniversityEmail yang diverifikasi di purdue.edu
Zhangshuan (Jason) HouPacific Northwest National LaboratoryEmail yang diverifikasi di pnnl.gov
Ben YangSchool of Atmospheric Sciences, Nanjing UniversityEmail yang diverifikasi di nju.edu.cn
Alexandre TartakovskyUniversity of Illinois Urbana-Champaign and Pacific Northwest National LaboratoryEmail yang diverifikasi di pnnl.gov
Weixuan LiMicrosoftEmail yang diverifikasi di microsoft.com
Yun QianPNNLEmail yang diverifikasi di pnnl.gov
Bin ZhengScientist, Pacific Northwest National LaboratoryEmail yang diverifikasi di pnnl.gov
Shuai LuFounder and CEO, EnerModEmail yang diverifikasi di enermod.com
Ning ZhouAssociate Professor, SUNY Binghamton UniversityEmail yang diverifikasi di binghamton.edu
Jie BaoResearch Engineer, Experimental and Computational Engineering Group, Pacific Northwest NationalEmail yang diverifikasi di pnnl.gov
Chun ZhaoUniversity of Science and Technology of ChinaEmail yang diverifikasi di ustc.edu.cn
Shaobu WangPacific Northwest National LabEmail yang diverifikasi di pnnl.gov
Xiaoliang WanLouisiana State UniversityEmail yang diverifikasi di math.lsu.edu
J. Nathan KutzProfessor of Applied Mathematics & Electrical and Computer EngineeringEmail yang diverifikasi di uw.edu
Xiaohong LiuReta Haynes Chair in Geosciences, Professor of Atmospheric Sciences, Texas A&M UniversityEmail yang diverifikasi di tamu.edu
Hailong WangPacific Northwest National LaboratoryEmail yang diverifikasi di pnnl.gov
Minghuai WangSchool of Atmospheric Sciences, Nanjing UniversityEmail yang diverifikasi di nju.edu.cn
Marcelo A ElizondoPacific Northwest National LaboratoryEmail yang diverifikasi di pnnl.gov

Ikuti

Guang Lin

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

Email yang diverifikasi di purdue.edu - Beranda

Scientific Machine Learning Uncertainty Quantification Generative AI LLM Deep Learning


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
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	209	2018
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	209	2013
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	188	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	159	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	156	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	145	2009
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	129	2012
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	123	2013
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	121	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	114	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	104	2021
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	103	2021
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	87	2018
Predicting shock dynamics in the presence of uncertainties G Lin, CH Su, GE Karniadakis Journal of Computational Physics 217 (1), 260-276, 2006	84	2006
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	79	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	76	2014
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	76	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	71	2013
Improving simulation efficiency of MCMC for inverse modeling of hydrologic systems with a Kalman‐inspired proposal distribution J Zhang, JA Vrugt, X Shi, G Lin, L Wu, L Zeng Water Resources Research 56 (3), e2019WR025474, 2020	70	2020

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