Guang Lin

According to our database, Guang Lin authored at least 168 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

HomPINNs: Homotopy physics-informed neural networks for solving the inverse problems of nonlinear differential equations with multiple solutions.

Haoyang Zheng, Yao Huang, Ziyang Huang, Wenrui Hao, Guang Lin

J. Comput. Phys., March, 2024

Energy-dissipative evolutionary deep operator neural networks.

Jiahao Zhang, Shiheng Zhang, Jie Shen, Guang Lin

J. Comput. Phys., February, 2024

Accelerating inverse inference of ensemble Kalman filter via reduced-order model trained using adaptive sparse observations.

Yuepeng Wang, Jie Li, Wenju Zhao, I. M. Navon, Guang Lin

J. Comput. Phys., January, 2024

Robust Diffusion Models for Adversarial Purification.

Guang Lin, Zerui Tao, Jianhai Zhang, Toshihisa Tanaka, Qibin Zhao

CoRR, 2024

Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks.

Christian Moya, Amirhossein Mollaali, Zecheng Zhang, Lu Lu, Guang Lin

CoRR, 2024

Adversarial Training on Purification (AToP): Advancing Both Robustness and Generalization.

Guang Lin, Chao Li, Jianhai Zhang, Toshihisa Tanaka, Qibin Zhao

CoRR, 2024

Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo.

Haoyang Zheng, Wei Deng, Christian Moya, Guang Lin

CoRR, 2024

Federated X-armed Bandit.

Wenjie Li, Qifan Song, Jean Honorio, Guang Lin

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Bayesian, Multifidelity Operator Learning for Complex Engineering Systems-A Position Paper.

Christian Moya, Guang Lin

J. Comput. Inf. Sci. Eng., December, 2023

Efficient Exploration of Chemical Compound Space Using Active Learning for Prediction of Thermodynamic Properties of Alkane Molecules.

Yan Xiang, Yu-Hang Tang, Zheng Gong, Hongyi Liu, Liang Wu, Guang Lin, Huai Sun

J. Chem. Inf. Model., November, 2023

Statistical Learning for Nonlinear Dynamical Systems with Applications to Aircraft-UAV Collisions.

Xinchao Liu, Xiao Liu, Tulin Kaman, Xiaohua Lu, Guang Lin

Technometrics, October, 2023

DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-Shot Transfer the Dynamic Response of Networked Systems.

Yixuan Sun, Christian Moya, Guang Lin, Meng Yue

IEEE Syst. J., September, 2023

Interpretable Molecular Property Predictions Using Marginalized Graph Kernels.

Yan Xiang, Yu-Hang Tang, Guang Lin, Daniel Reker

J. Chem. Inf. Model., August, 2023

NSGA-PINN: A Multi-Objective Optimization Method for Physics-Informed Neural Network Training.

Binghang Lu, Christian Moya, Guang Lin

Algorithms, April, 2023

DAE-PINN: a physics-informed neural network model for simulating differential algebraic equations with application to power networks.

Christian Moya, Guang Lin

Neural Comput. Appl., February, 2023

B-DeepONet: An enhanced Bayesian DeepONet for solving noisy parametric PDEs using accelerated replica exchange SGLD.

Guang Lin, Christian Moya, Zecheng Zhang

J. Comput. Phys., 2023

DeepONet-grid-UQ: A trustworthy deep operator framework for predicting the power grid's post-fault trajectories.

Christian Moya, Shiqi Zhang, Guang Lin, Meng Yue

Neurocomputing, 2023

Learning the dynamical response of nonlinear non-autonomous dynamical systems with deep operator neural networks.

Guang Lin, Christian Moya, Zecheng Zhang

Eng. Appl. Artif. Intell., 2023

Unbiasing Enhanced Sampling on a High-dimensional Free Energy Surface with Deep Generative Model.

Yikai Liu, Tushar K. Ghosh, Guang Lin, Ming Chen

CoRR, 2023

B-LSTM-MIONet: Bayesian LSTM-based Neural Operators for Learning the Response of Complex Dynamical Systems to Length-Variant Multiple Input Functions.

Zhihao Kong, Amirhossein Mollaali, Christian Moya, Na Lu, Guang Lin

CoRR, 2023

Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes.

Jinwon Sohn, Qifan Song, Guang Lin

CoRR, 2023

A Physics-Guided Bi-Fidelity Fourier-Featured Operator Learning Framework for Predicting Time Evolution of Drag and Lift Coefficients.

Amirhossein Mollaali, Izzet Sahin, Iqrar Raza, Christian Moya, Guillermo Paniagua, Guang Lin

CoRR, 2023

D2NO: Efficient Handling of Heterogeneous Input Function Spaces with Distributed Deep Neural Operators.

Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer

CoRR, 2023

Backdiff: a diffusion model for generalized transferable protein backmapping.

Yikai Liu, Ming Chen, Guang Lin

CoRR, 2023

Restoring the Discontinuous Heat Equation Source Using Sparse Boundary Data and Dynamic Sensors.

Guang Lin, Na Ou, Zecheng Zhang, Zhidong Zhang

CoRR, 2023

An Element-wise RSAV Algorithm for Unconstrained Optimization Problems.

Shiheng Zhang, Jiahao Zhang, Jie Shen, Guang Lin

CoRR, 2023

Bayesian deep operator learning for homogenized to fine-scale maps for multiscale PDE.

Zecheng Zhang, Christian Moya, Wing Tat Leung, Guang Lin, Hayden Schaeffer

CoRR, 2023

Multi-Subdomain Adversarial Network for Cross-Subject EEG-based Emotion Recognition.

Guang Lin, Jianhai Zhang

CoRR, 2023

Deep Operator Learning-based Surrogate Models with Uncertainty Quantification for Optimizing Internal Cooling Channel Rib Profiles.

Izzet Sahin, Christian Moya, Amirhossein Mollaali, Guang Lin, Guillermo Paniagua

CoRR, 2023

Numerical Stability for Differential Equations with Memory.

Guihong Wang, Yuqing Li, Tao Luo, Zheng Ma, Nung Kwan Yip, Guang Lin

CoRR, 2023

On Approximating the Dynamic Response of Synchronous Generators via Operator Learning: A Step Towards Building Deep Operator-based Power Grid Simulators.

Christian Moya, Guang Lin, Tianqiao Zhao, Meng Yue

CoRR, 2023

Fast Replica Exchange Stochastic Gradient Langevin Dynamics.

Guanxun Li, Guang Lin, Zecheng Zhang, Quan Zhou

CoRR, 2023

Non-reversible Parallel Tempering for Deep Posterior Approximation.

Wei Deng, Qian Zhang, Qi Feng, Faming Liang, Guang Lin

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

AMS-Net: Adaptive Multiscale Sparse Neural Network with Interpretable Basis Expansion for Multiphase Flow Problems.

Yating Wang, Wing Tat Leung, Guang Lin

Multiscale Model. Simul., March, 2022

Learning-PDE-Based Approximate Optimal Control for an MHD System With Uncertainty Quantification.

Tehuan Chen, Zhigang Ren, Guang Lin, Chao Xu

IEEE Trans. Syst. Man Cybern. Syst., 2022

Deformation Robust Roto-Scale-Translation Equivariant CNNs.

Liyao Gao, Guang Lin, Wei Zhu

Trans. Mach. Learn. Res., 2022

An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization.

Wei Deng, Guang Lin, Faming Liang

Stat. Comput., 2022

Data-driven causal model discovery and personalized prediction in Alzheimer's disease.

Haoyang Zheng, Jeffrey R. Petrella, P. Murali Doraiswamy, Guang Lin, Wenrui Hao

npj Digit. Medicine, 2022

Multi-variance replica exchange SGMCMC for inverse and forward problems via Bayesian PINN.

Guang Lin, Yating Wang, Zecheng Zhang

J. Comput. Phys., 2022

NH-PINN: Neural homogenization-based physics-informed neural network for multiscale problems.

Wing Tat Leung, Guang Lin, Zecheng Zhang

J. Comput. Phys., 2022

Implementing contact angle boundary conditions for second-order Phase-Field models of wall-bounded multiphase flows.

Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani

J. Comput. Phys., 2022

A consistent and conservative Phase-Field model for thermo-gas-liquid-solid flows including liquid-solid phase change.

Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani

J. Comput. Phys., 2022

RotEqNet: Rotation-equivariant network for fluid systems with symmetric high-order tensors.

Liyao Gao, Yifan Du, Hongshan Li, Guang Lin

J. Comput. Phys., 2022

Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems.

Hugo Esquivel, Arun Prakash, Guang Lin

J. Comput. Phys., 2022

Efficient hybrid explicit-implicit learning for multiscale problems.

Yalchin Efendiev, Wing Tat Leung, Guang Lin, Zecheng Zhang

J. Comput. Phys., 2022

Block triangular preconditioning for stochastic Galerkin method.

Dongwu Wang, Bin Zheng, Long Chen, Guang Lin, Jinchao Xu

J. Comput. Appl. Math., 2022

A consistent and conservative Phase-Field method for multiphase incompressible flows.

Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani

J. Comput. Appl. Math., 2022

Vapor-liquid equilibrium estimation of n-alkane/nitrogen mixtures using neural networks.

Suman Chakraborty, Yixuan Sun, Guang Lin, Li Qiao

J. Comput. Appl. Math., 2022

Feature Selection Techniques for a Machine Learning Model to Detect Autonomic Dysreflexia.

Shruthi Suresh, David T. Newton, Thomas H. Everett, Guang Lin, Bradley S. Duerstock

Frontiers Neuroinformatics, 2022

A replica exchange preconditioned Crank-Nicolson Langevin dynamic MCMC method for Bayesian inverse problems.

Na Ou, Zecheng Zhang, Guang Lin

CoRR, 2022

Efficient Chemical Space Exploration Using Active Learning Based on Marginalized Graph Kernel: an Application for Predicting the Thermodynamic Properties of Alkanes with Molecular Simulation.

Yan Xiang, Yu-Hang Tang, Zheng Gong, Hongyi Liu, Liang Wu, Guang Lin, Huai Sun

CoRR, 2022

2-d signature of images and texture classification.

Sheng Zhang, Guang Lin, Samy Tindel

CoRR, 2022

RMFGP: Rotated Multi-fidelity Gaussian process with Dimension Reduction for High-dimensional Uncertainty Quantification.

Jiahao Zhang, Shiqi Zhang, Guang Lin

CoRR, 2022

MultiAuto-DeepONet: A Multi-resolution Autoencoder DeepONet for Nonlinear Dimension Reduction, Uncertainty Quantification and Operator Learning of Forward and Inverse Stochastic Problems.

Jiahao Zhang, Shiqi Zhang, Guang Lin

CoRR, 2022

PAGP: A physics-assisted Gaussian process framework with active learning for forward and inverse problems of partial differential equations.

Jiahao Zhang, Shiqi Zhang, Guang Lin

CoRR, 2022

Inverse Modeling of Hydrologic Parameters in CLM4 via Generalized Polynomial Chaos in the Bayesian Framework.

Georgios Karagiannis, Zhangshuan Hou, Maoyi Huang, Guang Lin

Comput., 2022

HomPINNs: Homotopy physics-informed neural networks for learning multiple solutions of nonlinear elliptic differential equations.

Yao Huang, Wenrui Hao, Guang Lin

Comput. Math. Appl., 2022

Fed-DeepONet: Stochastic Gradient-Based Federated Training of Deep Operator Networks.

Christian Moya, Guang Lin

Algorithms, 2022

Interacting Contour Stochastic Gradient Langevin Dynamics.

Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang

Proceedings of the Tenth International Conference on Learning Representations, 2022

Glassoformer: A Query-Sparse Transformer for Post-Fault Power Grid Voltage Prediction.

Yunling Zheng, Carson Hu, Guang Lin, Meng Yue, Bao Wang, Jack Xin

Proceedings of the IEEE International Conference on Acoustics, 2022

Post-Fault Power Grid Voltage Prediction via 1D-CNN with Spatial Coupling.

Carson Hu, Guang Lin, Bao Wang, Meng Yue, Jack Xin

Proceedings of the 5th International Conference on Artificial Intelligence for Industries, 2022

2021

Gaussian Process Assisted Active Learning of Physical Laws.

Jiuhai Chen, Lulu Kang, Guang Lin

Technometrics, 2021

EEG-Based Sleep Staging Analysis with Functional Connectivity.

Hui Huang, Jianhai Zhang, Li Zhu, Jiajia Tang, Guang Lin, Wanzeng Kong, Xu Lei, Lei Zhu

Sensors, 2021

An integrated framework for building trustworthy data-driven epidemiological models: Application to the COVID-19 outbreak in New York City.

Sheng Zhang, Joan Ponce, Zhen Zhang, Guang Lin, George E. Karniadakis

PLoS Comput. Biol., 2021

Identifiability and predictability of integer- and fractional-order epidemiological models using physics-informed neural networks.

Ehsan Kharazmi, Min Cai, Xiaoning Zheng, Zhen Zhang, Guang Lin, George Em Karniadakis

Nat. Comput. Sci., 2021

SubTSBR to tackle high noise and outliers for data-driven discovery of differential equations.

Sheng Zhang, Guang Lin

J. Comput. Phys., 2021

An adaptive Hessian approximated stochastic gradient MCMC method.

Yating Wang, Wei Deng, Guang Lin

J. Comput. Phys., 2021

Bayesian sparse learning with preconditioned stochastic gradient MCMC and its applications.

Yating Wang, Wei Deng, Guang Lin

J. Comput. Phys., 2021

Feasibility of DEIM for retrieving the initial field via dimensionality reduction.

Yuepeng Wang, Xuemei Ding, Kun Hu, Fangxin Fang, I. M. Navon, Guang Lin

J. Comput. Phys., 2021

A consistent and conservative model and its scheme for <i>N</i>-phase-<i>M</i>-component incompressible flows.

Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani

J. Comput. Phys., 2021

Flow-driven spectral chaos (FSC) method for simulating long-time dynamics of arbitrary-order non-linear stochastic dynamical systems.

Hugo Esquivel, Arun Prakash, Guang Lin

J. Comput. Phys., 2021

A Comparative Study of Marginalized Graph Kernel and Message-Passing Neural Network.

Yan Xiang, Yu-Hang Tang, Guang Lin, Huai Sun

J. Chem. Inf. Model., 2021

A generalized multi-fidelity simulation method using sparse polynomial chaos expansion.

Jun Man, Guang Lin, Yijun Yao, Lingzao Zeng

J. Comput. Appl. Math., 2021

Flow-driven spectral chaos (FSC) method for long-time integration of second-order stochastic dynamical systems.

Hugo Esquivel, Arun Prakash, Guang Lin

J. Comput. Appl. Math., 2021

Binary classification of floor vibrations for human activity detection based on dynamic mode decomposition.

Shichao Zhou, Guang Lin, Qinfang Qian, Chao Xu

Neurocomputing, 2021

On Convergence of Federated Averaging Langevin Dynamics.

Wei Deng, Yi-An Ma, Zhao Song, Qian Zhang, Guang Lin

CoRR, 2021

Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs.

Guang Lin, Christian Moya, Zecheng Zhang

CoRR, 2021

Theoretical and numerical studies of inverse source problem for the linear parabolic equation with sparse boundary measurements.

Guang Lin, Zecheng Zhang, Zhidong Zhang

CoRR, 2021

PCNN: A physics-constrained neural network for multiphase flows.

Haoyang Zheng, Ziyang Huang, Guang Lin

CoRR, 2021

HEI: hybrid explicit-implicit learning for multiscale problems.

Yalchin Efendiev, Wing Tat Leung, Guang Lin, Zecheng Zhang

CoRR, 2021

Multi-variance replica exchange stochastic gradient MCMC for inverse and forward Bayesian physics-informed neural network.

Guang Lin, Yating Wang, Zecheng Zhang

CoRR, 2021

Robust data-driven discovery of partial differential equations with time-dependent coefficients.

Aoxue Chen, Guang Lin

CoRR, 2021

A consistent and conservative model and its scheme for N-phase-M-component incompressible flows.

Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani

CoRR, 2021

DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving.

Wei Deng, Junwei Pan, Tian Zhou, Deguang Kong, Aaron Flores, Guang Lin

Proceedings of the WSDM '21, 2021

Triplet-Branch Network with Prior-Knowledge Embedding for Fatigue Fracture Grading.

Yuexiang Li, Yanping Wang, Guang Lin, Yi Lin, Dong Wei, Qirui Zhang, Kai Ma, Guangming Lu, Zhiqiang Zhang, Yefeng Zheng

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction.

Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang

Proceedings of the 9th International Conference on Learning Representations, 2021

Speaker recognition with voice evoked EEG.

Lang Hu, Li Zhu, Hui Huang, Guang Lin, Bin Ren, Jianhai Zhang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

Multi-Branch Network for Cross-Subject EEG-based Emotion Recognition.

Guang Lin, Li Zhu, Bin Ren, Yiteng Hu, Jianhai Zhang

Proceedings of the Asian Conference on Machine Learning, 2021

2020

Latent transformations neural network for object view synthesis.

Sangpil Kim, Nick Winovich, Hyung-Gun Chi, Guang Lin, Karthik Ramani

Vis. Comput., 2020

A Low-Rank Approximated Multiscale Method for Pdes With Random Coefficients.

Na Ou, Guang Lin, Lijian Jiang

Multiscale Model. Simul., 2020

A Homotopy Method with Adaptive Basis Selection for Computing Multiple Solutions of Differential Equations.

Wenrui Hao, Jan S. Hesthaven, Guang Lin, Bin Zheng

J. Sci. Comput., 2020

Real-time computational optimal control of an MHD flow system with parameter uncertainty quantification.

Tehuan Chen, Zhigang Ren, Guang Lin, Zongze Wu, Bao-Lin Ye

J. Frankl. Inst., 2020

Efficient deep learning techniques for multiphase flow simulation in heterogeneous porousc media.

Yating Wang, Guang Lin

J. Comput. Phys., 2020

Consistent and conservative scheme for incompressible two-phase flows using the conservative Allen-Cahn model.

Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani

J. Comput. Phys., 2020

Consistent, essentially conservative and balanced-force Phase-Field method to model incompressible two-phase flows.

Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani

J. Comput. Phys., 2020

Robust weighted SVD-type latent factor models for rating prediction.

Yiqi Gu, Xi Yang, Mengjiao Peng, Guang Lin

Expert Syst. Appl., 2020

Single Shot Reversible GAN for BCG artifact removal in simultaneous EEG-fMRI.

Guang Lin, Jianhai Zhang, Yuxi Liu

CoRR, 2020

Predicting Mechanical Properties from Microstructure Images in Fiber-reinforced Polymers using Convolutional Neural Networks.

Yixuan Sun, Imad Hanhan, Michael D. Sangid, Guang Lin

CoRR, 2020

Spatial Damage Characterization in Self-Sensing Materials via Neural Network-Aided Electrical Impedance Tomography: A Computational Study.

Lang Zhao, Tyler Tallman, Guang Lin

CoRR, 2020

MFPC-Net: Multi-fidelity Physics-Constrained Neural Process.

Yating Wang, Guang Lin

CoRR, 2020

Multifidelity Data Fusion via Gradient-Enhanced Gaussian Process Regression.

Yixiang Deng, Guang Lin, Xiu Yang

CoRR, 2020

Peri-Net-Pro: The neural processes with quantified uncertainty for crack patterns.

Moonseop Kim, Guang Lin

CoRR, 2020

Multi-Fidelity Gaussian Process based Empirical Potential Development for Si: H Nanowires.

Moonseop Kim, Huayi Yin, Guang Lin

CoRR, 2020

DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving.

Wei Deng, Junwei Pan, Tian Zhou, Aaron Flores, Guang Lin

CoRR, 2020

Error estimates of a spectral Petrov-Galerkin method for two-sided fractional reaction-diffusion equations.

Zhaopeng Hao, Guang Lin, Zhongqiang Zhang

Appl. Math. Comput., 2020

Machine-Learning-Based Online Transient Analysis via Iterative Computation of Generator Dynamics.

Jiaming Li, Meng Yue, Yue Zhao, Guang Lin

Proceedings of the 2020 IEEE International Conference on Communications, 2020

A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions.

Wei Deng, Guang Lin, Faming Liang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Non-convex Learning via Replica Exchange Stochastic Gradient MCMC.

Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Finite Element Method for Two-Sided Fractional Differential Equations with Variable Coefficients: Galerkin Approach.

Zhaopeng Hao, Moongyu Park, Guang Lin, Zhiqiang Cai

J. Sci. Comput., 2019

ConvPDE-UQ: Convolutional neural networks with quantified uncertainty for heterogeneous elliptic partial differential equations on varied domains.

Nick Winovich, Karthik Ramani, Guang Lin

J. Comput. Phys., 2019

Optimal observations-based retrieval of topography in 2D shallow water equations using PC-EnKF.

Yuepeng Wang, Kun Hu, Lanlan Ren, Guang Lin

J. Comput. Phys., 2019

A mixed upwind/central WENO scheme for incompressible two-phase flows.

Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani

J. Comput. Phys., 2019

Efficient Deep Learning Techniques for Multiphase Flow Simulation in Heterogeneous Porous Media.

Yating Wang, Guang Lin

CoRR, 2019

Robust subsampling-based sparse Bayesian inference to tackle four challenges (large noise, outliers, data integration, and extrapolation) in the discovery of physical laws from data.

Sheng Zhang, Guang Lin

CoRR, 2019

Reinforcement Learning for Traffic Control with Adaptive Horizon.

Wentao Chen, Tehuan Chen, Guang Lin

CoRR, 2019

Outlier Detection and Correction for Monitoring Data of Water Quality Based on Improved VMD and LSSVM.

Guangpei Sun, Peng Jiang, Huan Xu, Shan-en Yu, Dong Guo, Guang Lin, Hui Wu

Complex., 2019

Infrared Thermal Imaging-Based Crack Detection Using Deep Learning.

Jun Yang, Wei Wang, Guang Lin, Qing Li, Yeqing Sun, Yixuan Sun

IEEE Access, 2019

Stochastic Security Assessment for Power Systems With High Renewable Energy Penetration Considering Frequency Regulation.

Yu Huang, Qingshan Xu, Sajjad Abedi, Tong Zhang, Xianqiang Jiang, Guang Lin

IEEE Access, 2019

An Adaptive Empirical Bayesian Method for Sparse Deep Learning.

Wei Deng, Xiao Zhang, Faming Liang, Guang Lin

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Rotation-equivariant convolutional neural network ensembles in image processing.

Liyao Gao, Hongshan Li, Zheying Lu, Guang Lin

Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers, 2019

UAV-Based Motion Target Detection and Tracking Method in Dynamic Scenes.

Guodong Yang, Jianhai Zhang, Li Zhu, Weitao Huan, Guang Lin, Zheng Ma

Proceedings of the Fourth IEEE International Conference on Data Science in Cyberspace, 2019

2018

Two-Level Spectral Methods for Nonlinear Elliptic Equations with Multiple Solutions.

Yingwei Wang, Wenrui Hao, Guang Lin

SIAM J. Sci. Comput., 2018

Using automatic differentiation for compressive sensing in uncertainty quantification.

Mu Wang, Guang Lin, Alex Pothen

Optim. Methods Softw., 2018

CT-GAN: Conditional Transformation Generative Adversarial Network for Image Attribute Modification.

Sangpil Kim, Nick Winovich, Guang Lin, Karthik Ramani

CoRR, 2018

Local Feature Sufficiency Exploration for Predicting Security-Constrained Generation Dispatch in Multi-area Power Systems.

Yixuan Sun, Xiaoyuan Fan, Qiuhua Huang, Xinya Li, Renke Huang, Tianzhixi Yin, Guang Lin

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

2017

Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots.

Junpeng Wang, Xiaotong Liu, Han-Wei Shen, Guang Lin

IEEE Trans. Vis. Comput. Graph., 2017

Visualization of Time-Varying Weather Ensembles across Multiple Resolutions.

Ayan Biswas, Guang Lin, Xiaotong Liu, Han-Wei Shen

IEEE Trans. Vis. Comput. Graph., 2017

Comparative study of clustering techniques for real-time dynamic model reduction.

Emilie Purvine, Eduardo Cotilla Sanchez, Mahantesh Halappanavar, Zhenyu Huang, Guang Lin, Shuai Lu, Shaobu Wang

Stat. Anal. Data Min., 2017

Parallel and interacting stochastic approximation annealing algorithms for global optimisation.

Georgios Karagiannis, Bledar A. Konomi, Guang Lin, Faming Liang

Stat. Comput., 2017

On the Bayesian calibration of computer model mixtures through experimental data, and the design of predictive models.

Georgios Karagiannis, Guang Lin

J. Comput. Phys., 2017

A second-order difference scheme for the time fractional substantial diffusion equation.

Zhaopeng Hao, Wanrong Cao, Guang Lin

J. Comput. Appl. Math., 2017

A two-level stochastic collocation method for semilinear elliptic equations with random coefficients.

Luoping Chen, Bin Zheng, Guang Lin, Nikolaos K. Voulgarakis

J. Comput. Appl. Math., 2017

A high-order difference scheme for the fractional sub-diffusion equation.

Zhao-peng Hao, Guang Lin, Zhi-Zhong Sun

Int. J. Comput. Math., 2017

2016

The stabilization of BAM neural networks with time-varying delays in the leakage terms via sampled-data control.

Li Li, Yongqing Yang, Guang Lin

Neural Comput. Appl., 2016

Classification of Spatiotemporal Data via Asynchronous Sparse Sampling: Application to Flow around a Cylinder.

Ido Bright, Guang Lin, J. Nathan Kutz

Multiscale Model. Simul., 2016

On Application of the Weak Galerkin Finite Element Method to a Two-Phase Model for Subsurface Flow.

Victor Ginting, Guang Lin, Jiangguo Liu

J. Sci. Comput., 2016

Enhancing sparsity of Hermite polynomial expansions by iterative rotations.

Xiu Yang, Huan Lei, Nathan A. Baker, Guang Lin

J. Comput. Phys., 2016

Gaussian process surrogates for failure detection: A Bayesian experimental design approach.

Hongqiao Wang, Guang Lin, Jinglai Li

J. Comput. Phys., 2016

Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs.

Qifeng Liao, Guang Lin

J. Comput. Phys., 2016

Inverse regression-based uncertainty quantification algorithms for high-dimensional models: Theory and practice.

Weixuan Li, Guang Lin, Bing Li

J. Comput. Phys., 2016

Error analysis of finite element method for Poisson-Nernst-Planck equations.

Yuzhou Sun, Pengtao Sun, Bin Zheng, Guang Lin

J. Comput. Appl. Math., 2016

Integrate Big Data for Better Operation, Control, and Protection of Power Systems.

Guang Lin

Proceedings of the Handbook of Big Data., 2016

2015

Constructing Surrogate Models of Complex Systems with Enhanced Sparsity: Quantifying the Influence of Conformational Uncertainty in Biomolecular Solvation.

Huan Lei, Xiu Yang, Bin Zheng, Guang Lin, Nathan A. Baker

Multiscale Model. Simul., 2015

Full scale multi-output Gaussian process emulator with nonseparable auto-covariance functions.

Bohai Zhang, Bledar A. Konomi, Huiyan Sang, Georgios Karagiannis, Guang Lin

J. Comput. Phys., 2015

A frozen Gaussian approximation-based multi-level particle swarm optimization for seismic inversion.

Jinglai Li, Guang Lin, Xu Yang

J. Comput. Phys., 2015

An adaptive importance sampling algorithm for Bayesian inversion with multimodal distributions.

Weixuan Li, Guang Lin

J. Comput. Phys., 2015

A Bayesian mixed shrinkage prior procedure for spatial-stochastic basis selection and evaluation of gPC expansions: Applications to elliptic SPDEs.

Georgios Karagiannis, Bledar A. Konomi, Guang Lin

J. Comput. Phys., 2015

A fictitious domain method with a hybrid cell model for simulating motion of cells in fluid flow.

Wenrui Hao, Zhiliang Xu, Chun Liu, Guang Lin

J. Comput. Phys., 2015

A comparative study on the weak Galerkin, discontinuous Galerkin, and mixed finite element methods.

Guang Lin, Jiangguo Liu, Farrah Sadre-Marandi

J. Comput. Appl. Math., 2015

Comparative Studies of Clustering Techniques for Real-Time Dynamic Model Reduction.

Emilie Hogan, Eduardo Cotilla Sanchez, Mahantesh Halappanavar, Zhenyu Huang, Guang Lin, Shuai Lu, Shaobu Wang

CoRR, 2015

2014

Bayesian Treed Multivariate Gaussian Process With Adaptive Design: Application to a Carbon Capture Unit.

Bledar A. Konomi, Georgios Karagiannis, Avik Sarkar, Xin Sun, Guang Lin

Technometrics, 2014

Rare-Event Simulation for the Stochastic Korteweg-de Vries Equation.

Gongjun Xu, Guang Lin, Jingchen Liu

SIAM/ASA J. Uncertain. Quantification, 2014

Weak Galerkin finite element methods for Darcy flow: Anisotropy and heterogeneity.

Guang Lin, Jiangguo Liu, Lin Mu, Xiu Ye

J. Comput. Phys., 2014

An adaptive ANOVA-based PCKF for high-dimensional nonlinear inverse modeling.

Weixuan Li, Guang Lin, Dongxiao Zhang

J. Comput. Phys., 2014

Selection of polynomial chaos bases via Bayesian model uncertainty methods with applications to sparse approximation of PDEs with stochastic inputs.

Georgios Karagiannis, Guang Lin

J. Comput. Phys., 2014

2013

Hybrid parallel computing of minimum action method.

Xiaoliang Wan, Guang Lin

Parallel Comput., 2013

Numerical solution of the Stratonovich- and Ito-Euler equations: Application to the stochastic piston problem.

Zhongqiang Zhang, Xiu Yang, Guang Lin, George E. Karniadakis

J. Comput. Phys., 2013

Multi-output separable Gaussian process: Towards an efficient, fully Bayesian paradigm for uncertainty quantification.

Ilias Bilionis, Nicholas Zabaras, Bledar A. Konomi, Guang Lin

J. Comput. Phys., 2013

Evaluating the impact of aquifer layer properties on geomechanical response during CO₂ geological sequestration.

Jie Bao, Zhijie Xu, Guang Lin, Yilin Fang

Comput. Geosci., 2013

Exploring Cloud Computing for Large-Scale Scientific Applications.

Guang Lin, Binh Han, Jian Yin, Ian Gorton

Proceedings of the IEEE Ninth World Congress on Services, 2013

Improved CamShift tracking algorithm based on motion detection.

Yu-Hui Qui, Jian-Wei Zhang, Guang Lin, Yong-Hui Li, Dong-Fa Gao

Proceedings of the International Conference on Machine Learning and Cybernetics, 2013

2012

Adaptive ANOVA decomposition of stochastic incompressible and compressible flows.

Xiu Yang, Minseok Choi, Guang Lin, George E. Karniadakis

J. Comput. Phys., 2012

2011

Point-wise hierarchical reconstruction for discontinuous Galerkin and finite volume methods for solving conservation laws.

Zhiliang Xu, Yingjie Liu, Huijing Du, Guang Lin, Chi-Wang Shu

J. Comput. Phys., 2011

MeDiCi-Cloud: A Workflow Infrastructure for Large-scale Scientific Applications.

Jian Yin, Guang Lin, Ian Gorton, Binh Han

Proceedings of the IEEE 4th International Conference on Utility and Cloud Computing, 2011

A new IITNAM representation method of gray images.

Yunping Zheng, Zujia Li, Mudar Sarem, Guang Lin, Liqiang Hu

Proceedings of the Eighth International Conference on Fuzzy Systems and Knowledge Discovery, 2011

2007

Stochastic Computational Fluid Mechanics.

Guang Lin, Xiaoliang Wan, Chau-Hsing Su, George E. Karniadakis

Comput. Sci. Eng., 2007

2006

Predicting shock dynamics in the presence of uncertainties.

Guang Lin, Chau-Hsing Su, George E. Karniadakis

J. Comput. Phys., 2006

Numerical studies of the stochastic Korteweg-de Vries equation.

Guang Lin, Leopold Grinberg, George E. Karniadakis

J. Comput. Phys., 2006