Folgen
Guang Lin
Guang Lin
Associate Dean for Research, Professor of Mathematics, Mech Eng, Statistics, Purdue University
Bestätigte E-Mail-Adresse bei purdue.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
2092018
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
2092013
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
1882013
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
1592012
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
1562012
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
1452009
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
1292012
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
1232013
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
1222016
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
1212019
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
1142017
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
1052021
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
1042021
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
892018
Predicting shock dynamics in the presence of uncertainties
G Lin, CH Su, GE Karniadakis
Journal of Computational Physics 217 (1), 260-276, 2006
842006
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
792014
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
762014
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
762010
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
712020
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
702013
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20