Guang Lin - RankMe

223 papers A* 9A 3B 1C 1Misc 2Journal 204Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Active operator learning with predictive uncertainty quantification for partial differential equations. J. Comput. Phys. Nick Winovich, Mitchell Daneker, Lu Lu, Guang Lin
2026	J	`jnl`	Adversarial Vulnerability from On-Manifold Inseparability and Poor Off-Manifold Convergence. Trans. Mach. Learn. Res. Rajdeep Haldar, Yue Xing, Qifan Song, Guang Lin
2026	J	`jnl`	DeepONet as a multi-Operator extrapolation model: Distributed pretraining with physics-Informed fine-Tuning. J. Comput. Phys. Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer
2026	A*	`conf`	Exploring Non-Convex Discrete Energy Landscapes: An Efficient Langevin-Like Sampler with Replica Exchange. AAAI Haoyang Zheng, Hengrong Du, Ruqi Zhang, Guang Lin
2026	J	`jnl`	Generalized Discrete Diffusion with Self-Correction. CoRR Linxuan Wang, Ziyi Wang, Yikun Bai, Wei Deng, Guang Lin, Qifan Song
2026	J	`jnl`	Generative prior-guided neural interface reconstruction for 3D electrical impedance tomography. J. Comput. Phys. Haibo Liu, Junqing Chen, Guang Lin
2026	J	`jnl`	LES-SINDy: Laplace-enhanced sparse identification of nonlinear dynamical systems. J. Comput. Phys. Haoyang Zheng, Guang Lin
2026	J	`jnl`	Neural-POD: A Plug-and-Play Neural Operator Framework for Infinite-Dimensional Functional Nonlinear Proper Orthogonal Decomposition. CoRR Changhong Mou, Binghang Lu, Guang Lin
2026	J	`jnl`	Task-tailored Pre-processing: Fair Downstream Supervised Learning. CoRR Jinwon Sohn, Guang Lin, Qifan Song
2026	J	`jnl`	Ultra Fast PDE Solving via Physics Guided Few-step Diffusion. CoRR Cindy Xiangrui Kong, Yueqi Wang, Haoyang Zheng, Weijian Luo, Guang Lin
2026	J	`jnl`	f-GRPO and Beyond: Divergence-Based Reinforcement Learning Algorithms for General LLM Alignment. CoRR Rajdeep Haldar, Lantao Mei, Guang Lin, Yue Xing, Qifan Song
2026	J	`jnl`	iPINNER: An iterative physics-informed neural network with ensemble Kalman filter. J. Comput. Phys. Binghang Lu, Changhong Mou, Guang Lin
2026	J	`jnl`	pADAM: A Plug-and-Play All-in-One Diffusion Architecture for Multi-Physics Learning. CoRR Amirhossein Mollaali, Bongseok Kim, Christian Moya, Guang Lin
2025	J	`jnl`	A Relaxed Vector Auxiliary Variable Algorithm for Unconstrained Optimization Problems. SIAM J. Sci. Comput. Shiheng Zhang, Jiahao Zhang, Jie Shen, Guang Lin
2025	J	`jnl`	A Review of Artificial Intelligence-Driven Approaches for Nanoscale Heat Conduction and Radiation. J. Comput. Inf. Sci. Eng. Ziqi Guo, Daniel Carne, Krutarth Khot, Dudong Feng, Guang Lin, Xiulin Ruan
2025	J	`jnl`	A self-adaptive energy-based learning rate for stochastic gradient descent via Vector Auxiliary Variable method. Eng. Appl. Artif. Intell. Jiahao Zhang, Christian Moya, Guang Lin
2025	J	`jnl`	Active operator learning with predictive uncertainty quantification for partial differential equations. CoRR Nick Winovich, Mitchell Daneker, Lu Lu, Guang Lin
2025	J	`jnl`	An Evolutionary Multi-objective Optimization for Replica-Exchange-based Physics-informed Operator Learning Network. CoRR Binghang Lu, Changhong Mou, Guang Lin
2025	J	`jnl`	Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory. J. Comput. Graph. Stat. Jiajun Liang, Qian Zhang, Wei Deng, Qifan Song, Guang Lin
2025	J	`jnl`	Coefficient-to-Basis Network: A Fine-Tunable Operator Learning Framework for Inverse Problems with Adaptive Discretizations and Theoretical Guarantees. CoRR Zecheng Zhang, Hao Liu, Wenjing Liao, Guang Lin
2025	J	`jnl`	Conformalized prediction of post-fault voltage trajectories using pre-trained and finetuned attention-driven neural operators. Neural Networks Amirhossein Mollaali, Gabriel Zufferey, Gonzalo Constante-Flores, Christian Moya, Can Li, Meng Yue, Guang Lin
2025	J	`jnl`	Conformalized-KANs: Uncertainty Quantification with Coverage Guarantees for Kolmogorov-Arnold Networks (KANs) in Scientific Machine Learning. CoRR Amirhossein Mollaali, Christian B. Moya, Amanda A. Howard, Alexander Heinlein, Panos Stinis, Guang Lin
2025	J	`jnl`	Energy-Dissipative Evolutionary Kolmogorov-Arnold Networks for Complex PDE Systems. CoRR Guang Lin, Changhong Mou, Jiahao Zhang
2025	J	`jnl`	Energy-dissipative evolutionary Kolmogorov-Arnold networks for complex PDE systems. J. Comput. Phys. Guang Lin, Changhong Mou, Jiahao Zhang
2025	J	`jnl`	Exploring Non-Convex Discrete Energy Landscapes: A Langevin-Like Sampler with Replica Exchange. CoRR Haoyang Zheng, Ruqi Zhang, Guang Lin
2025	J	`jnl`	FPINN-deeponet: A physics-informed operator learning framework for multi-term time-fractional mixed diffusion-wave equations. J. Comput. Phys. Binghang Lu, Zhaopeng Hao, Christian Moya, Guang Lin
2025	J	`jnl`	Finite Element Representation Network (FERN) for Operator Learning with a Localized Trainable Basis. CoRR Zecheng Zhang, Hao Liu, Guosheng Fu, Hayden Schaeffer, Guang Lin
2025	J	`jnl`	High-quality three-dimensional cartoon avatar reconstruction with Gaussian splatting. Eng. Appl. Artif. Intell. MinHyuk Jang, Jong Wook Kim, Youngdong Jang, Donghyun Kim, Wonseok Roh, Inyong Hwang, Guang Lin, Sangpil Kim
2025	J	`jnl`	ICP-4D: Bridging Iterative Closest Point and LiDAR Panoptic Segmentation. CoRR Gyeongrok Oh, Youngdong Jang, Jonghyun Choi, Suk-Ju Kang, Guang Lin, Sangpil Kim
2025	J	`jnl`	LAPD: Langevin-Assisted Bayesian Active Learning for Physical Discovery. CoRR Cindy Xiangrui Kong, Haoyang Zheng, Guang Lin
2025	J	`jnl`	LLM Safety Alignment is Divergence Estimation in Disguise. CoRR Rajdeep Haldar, Ziyi Wang, Qifan Song, Guang Lin, Yue Xing
2025	J	`jnl`	Linear Spatial World Models Emerge in Large Language Models. CoRR Matthieu Tehenan, Christian B. Moya, Tenghai Long, Guang Lin
2025	J	`jnl`	MoPINNEnKF: Iterative Model Inference using generic-PINN-based ensemble Kalman filter. CoRR Binghang Lu, Changhong Mou, Guang Lin
2025	J	`jnl`	Muti-Fidelity Prediction and Uncertainty Quantification with Laplace Neural Operators for Parametric Partial Differential Equations. CoRR Haoyang Zheng, Guang Lin
2025	J	`jnl`	Rethinking Langevin Thompson Sampling from A Stochastic Approximation Perspective. CoRR Weixin Wang, Haoyang Zheng, Guang Lin, Wei Deng, Pan Xu
2025	J	`jnl`	SQS: Bayesian DNN Compression through Sparse Quantized Sub-distributions. CoRR Ziyi Wang, Nan Jiang, Guang Lin, Qifan Song
2025	J	`jnl`	Ultra-Fast Language Generation via Discrete Diffusion Divergence Instruct. CoRR Haoyang Zheng, Xinyang Liu, Cindy Xiangrui Kong, Nan Jiang, Zheyuan Hu, Weijian Luo, Wei Deng, Guang Lin
2024	J	`jnl`	A replica exchange preconditioned Crank-Nicolson Langevin dynamic MCMC method with multi-variance strategy for Bayesian inverse problems. J. Comput. Phys. Na Ou, Zecheng Zhang, Guang Lin
2024	A	`conf`	Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo. AISTATS Haoyang Zheng, Wei Deng, Christian Moya, Guang Lin
2024	J	`jnl`	Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo. CoRR Haoyang Zheng, Wei Deng, Christian Moya, Guang Lin
2024	J	`jnl`	Accelerating inverse inference of ensemble Kalman filter via reduced-order model trained using adaptive sparse observations. J. Comput. Phys. Yuepeng Wang, Jie Li, Wenju Zhao, I. M. Navon, Guang Lin
2024	J	`jnl`	Adversarial Autoencoders in Operator Learning. CoRR Dustin Enyeart, Guang Lin
2024	J	`jnl`	Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility. CoRR Rajdeep Haldar, Yue Xing, Qifan Song, Guang Lin
2024	J	`jnl`	An Energy-Based Self-Adaptive Learning Rate for Stochastic Gradient Descent: Enhancing Unconstrained Optimization with VAV method. CoRR Jiahao Zhang, Christian Moya, Guang Lin
2024	J	`jnl`	Bayesian Deep Operator Learning for Homogenized to Fine-Scale Maps for Multiscale PDE. Multiscale Model. Simul. Zecheng Zhang, Christian Moya, Wing Tat Leung, Guang Lin, Hayden Schaeffer
2024	J	`jnl`	Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory. CoRR Jiajun Liang, Qian Zhang, Wei Deng, Qifan Song, Guang Lin
2024	J	`jnl`	Conformalized Prediction of Post-Fault Voltage Trajectories Using Pre-trained and Finetuned Attention-Driven Neural Operators. CoRR Amirhossein Mollaali, Gabriel Zufferey, Gonzalo Constante-Flores, Christian Moya, Can Li, Guang Lin, Meng Yue
2024	J	`jnl`	Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks. CoRR Christian Moya, Amirhossein Mollaali, Zecheng Zhang, Lu Lu, Guang Lin
2024	A*	`conf`	Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics. ICML Haoyang Zheng, Hengrong Du, Qi Feng, Wei Deng, Guang Lin
2024	J	`jnl`	Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics. CoRR Haoyang Zheng, Hengrong Du, Qi Feng, Wei Deng, Guang Lin
2024	J	`jnl`	DeepONet as a Multi-Operator Extrapolation Model: Distributed Pretraining with Physics-Informed Fine-Tuning. CoRR Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer
2024	J	`jnl`	Energy-dissipative evolutionary deep operator neural networks. J. Comput. Phys. Jiahao Zhang, Shiheng Zhang, Jie Shen, Guang Lin
2024	A*	`conf`	Federated X-armed Bandit. AAAI Wenjie Li, Qifan Song, Jean Honorio, Guang Lin
2024	J	`jnl`	HomPINNs: Homotopy physics-informed neural networks for solving the inverse problems of nonlinear differential equations with multiple solutions. J. Comput. Phys. Haoyang Zheng, Yao Huang, Ziyang Huang, Wenrui Hao, Guang Lin
2024	J	`jnl`	LES-SINDy: Laplace-Enhanced Sparse Identification of Nonlinear Dynamical Systems. CoRR Haoyang Zheng, Guang Lin
2024	J	`jnl`	Loss Terms and Operator Forms of Koopman Autoencoders. CoRR Dustin Enyeart, Guang Lin
2024	A	`conf`	On Convergence of Federated Averaging Langevin Dynamics. UAI Wei Deng, Qian Zhang, Yian Ma, Zhao Song, Guang Lin
2024	J	`jnl`	Some Best Practices in Operator Learning. CoRR Dustin Enyeart, Guang Lin
2024	J	`jnl`	Where to Build Food Banks and Pantries: A Two-Level Machine Learning Approach. CoRR Gavin Ruan, Ziqi Guo, Guang Lin
2023	J	`jnl`	A Physics-Guided Bi-Fidelity Fourier-Featured Operator Learning Framework for Predicting Time Evolution of Drag and Lift Coefficients. CoRR Amirhossein Mollaali, Izzet Sahin, Iqrar Raza, Christian Moya, Guillermo Paniagua, Guang Lin
2023	J	`jnl`	An Element-wise RSAV Algorithm for Unconstrained Optimization Problems. CoRR Shiheng Zhang, Jiahao Zhang, Jie Shen, Guang Lin
2023	J	`jnl`	B-DeepONet: An enhanced Bayesian DeepONet for solving noisy parametric PDEs using accelerated replica exchange SGLD. J. Comput. Phys. Guang Lin, Christian Moya, Zecheng Zhang
2023	J	`jnl`	B-LSTM-MIONet: Bayesian LSTM-based Neural Operators for Learning the Response of Complex Dynamical Systems to Length-Variant Multiple Input Functions. CoRR Zhihao Kong, Amirhossein Mollaali, Christian Moya, Na Lu, Guang Lin
2023	J	`jnl`	Backdiff: a diffusion model for generalized transferable protein backmapping. CoRR Yikai Liu, Ming Chen, Guang Lin
2023	J	`jnl`	Bayesian deep operator learning for homogenized to fine-scale maps for multiscale PDE. CoRR Zecheng Zhang, Christian Moya, Wing Tat Leung, Guang Lin, Hayden Schaeffer
2023	J	`jnl`	Bayesian, Multifidelity Operator Learning for Complex Engineering Systems-A Position Paper. J. Comput. Inf. Sci. Eng. Christian Moya, Guang Lin
2023	J	`jnl`	D2NO: Efficient Handling of Heterogeneous Input Function Spaces with Distributed Deep Neural Operators. CoRR Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer
2023	J	`jnl`	DAE-PINN: a physics-informed neural network model for simulating differential algebraic equations with application to power networks. Neural Comput. Appl. Christian Moya, Guang Lin
2023	J	`jnl`	Deep Operator Learning-based Surrogate Models with Uncertainty Quantification for Optimizing Internal Cooling Channel Rib Profiles. CoRR Izzet Sahin, Christian Moya, Amirhossein Mollaali, Guang Lin, Guillermo Paniagua
2023	J	`jnl`	DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-Shot Transfer the Dynamic Response of Networked Systems. IEEE Syst. J. Yixuan Sun, Christian Moya, Guang Lin, Meng Yue
2023	J	`jnl`	DeepONet-grid-UQ: A trustworthy deep operator framework for predicting the power grid's post-fault trajectories. Neurocomputing Christian Moya, Shiqi Zhang, Guang Lin, Meng Yue
2023	J	`jnl`	Efficient Exploration of Chemical Compound Space Using Active Learning for Prediction of Thermodynamic Properties of Alkane Molecules. J. Chem. Inf. Model. Yan Xiang, Yu-Hang Tang, Zheng Gong, Hongyi Liu, Liang Wu, Guang Lin, Huai Sun
2023	J	`jnl`	Energy-Dissipative Evolutionary Deep Operator Neural Networks. CoRR Jiahao Zhang, Shiheng Zhang, Jie Shen, Guang Lin
2023	J	`jnl`	Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes. CoRR Jinwon Sohn, Qifan Song, Guang Lin
2023	J	`jnl`	Fast Replica Exchange Stochastic Gradient Langevin Dynamics. CoRR Guanxun Li, Guang Lin, Zecheng Zhang, Quan Zhou
2023	J	`jnl`	HomPINNs: homotopy physics-informed neural networks for solving the inverse problems of nonlinear differential equations with multiple solutions. CoRR Haoyang Zheng, Yao Huang, Ziyang Huang, Wenrui Hao, Guang Lin
2023	J	`jnl`	Interpretable Molecular Property Predictions Using Marginalized Graph Kernels. J. Chem. Inf. Model. Yan Xiang, Yu-Hang Tang, Guang Lin, Daniel Reker
2023	J	`jnl`	Learning the dynamical response of nonlinear non-autonomous dynamical systems with deep operator neural networks. Eng. Appl. Artif. Intell. Guang Lin, Christian Moya, Zecheng Zhang
2023	J	`jnl`	NSGA-PINN: A Multi-Objective Optimization Method for Physics-Informed Neural Network Training. Algorithms Binghang Lu, Christian Moya, Guang Lin
2023	J	`jnl`	NSGA-PINN: A Multi-Objective Optimization Method for Physics-Informed Neural Network Training. CoRR Binghang Lu, Christian B. Moya, Guang Lin
2023	A*	`conf`	Non-reversible Parallel Tempering for Deep Posterior Approximation. AAAI Wei Deng, Qian Zhang, Qi Feng, Faming Liang, Guang Lin
2023	J	`jnl`	Numerical Stability for Differential Equations with Memory. CoRR Guihong Wang, Yuqing Li, Tao Luo, Zheng Ma, Nung Kwan Yip, Guang Lin
2023	J	`jnl`	On Approximating the Dynamic Response of Synchronous Generators via Operator Learning: A Step Towards Building Deep Operator-based Power Grid Simulators. CoRR Christian Moya, Guang Lin, Tianqiao Zhao, Meng Yue
2023	J	`jnl`	Restoring the Discontinuous Heat Equation Source Using Sparse Boundary Data and Dynamic Sensors. CoRR Guang Lin, Na Ou, Zecheng Zhang, Zhidong Zhang
2023	J	`jnl`	Statistical Learning for Nonlinear Dynamical Systems with Applications to Aircraft-UAV Collisions. Technometrics Xinchao Liu, Xiao Liu, Tulin Kaman, Xiaohua Lu, Guang Lin
2023	J	`jnl`	Unbiasing Enhanced Sampling on a High-dimensional Free Energy Surface with Deep Generative Model. CoRR Yikai Liu, Tushar K. Ghosh, Guang Lin, Ming Chen
2022	J	`jnl`	2-d signature of images and texture classification. CoRR Sheng Zhang, Guang Lin, Samy Tindel
2022	J	`jnl`	A consistent and conservative Phase-Field method for multiphase incompressible flows. J. Comput. Appl. Math. Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani
2022	J	`jnl`	A consistent and conservative Phase-Field model for thermo-gas-liquid-solid flows including liquid-solid phase change. J. Comput. Phys. Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani
2022	J	`jnl`	A replica exchange preconditioned Crank-Nicolson Langevin dynamic MCMC method for Bayesian inverse problems. CoRR Na Ou, Zecheng Zhang, Guang Lin
2022	J	`jnl`	AMS-Net: Adaptive Multiscale Sparse Neural Network with Interpretable Basis Expansion for Multiphase Flow Problems. CoRR Yating Wang, Wing Tat Leung, Guang Lin
2022	J	`jnl`	AMS-Net: Adaptive Multiscale Sparse Neural Network with Interpretable Basis Expansion for Multiphase Flow Problems. Multiscale Model. Simul. Yating Wang, Wing Tat Leung, Guang Lin
2022	J	`jnl`	An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization. Stat. Comput. Wei Deng, Guang Lin, Faming Liang
2022	J	`jnl`	Block triangular preconditioning for stochastic Galerkin method. J. Comput. Appl. Math. Dongwu Wang, Bin Zheng, Long Chen, Guang Lin, Jinchao Xu
2022	J	`jnl`	Data-driven causal model discovery and personalized prediction in Alzheimer's disease. npj Digit. Medicine Haoyang Zheng, Jeffrey R. Petrella, P. Murali Doraiswamy, Guang Lin, Wenrui Hao
2022	J	`jnl`	DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-shot Transfer the Dynamic Response of Networked Systems. CoRR Yixuan Sun, Christian Moya, Guang Lin, Meng Yue
2022	J	`jnl`	DeepONet-Grid-UQ: A Trustworthy Deep Operator Framework for Predicting the Power Grid's Post-Fault Trajectories. CoRR Christian Moya, Shiqi Zhang, Meng Yue, Guang Lin
2022	J	`jnl`	Efficient Chemical Space Exploration Using Active Learning Based on Marginalized Graph Kernel: an Application for Predicting the Thermodynamic Properties of Alkanes with Molecular Simulation. CoRR Yan Xiang, Yu-Hang Tang, Zheng Gong, Hongyi Liu, Liang Wu, Guang Lin, Huai Sun
2022	J	`jnl`	Efficient hybrid explicit-implicit learning for multiscale problems. J. Comput. Phys. Yalchin Efendiev, Wing Tat Leung, Guang Lin, Zecheng Zhang
2022	J	`jnl`	Feature Selection Techniques for a Machine Learning Model to Detect Autonomic Dysreflexia. Frontiers Neuroinformatics Shruthi Suresh, David T. Newton, Thomas H. Everett, Guang Lin, Bradley S. Duerstock
2022	J	`jnl`	Fed-DeepONet: Stochastic Gradient-Based Federated Training of Deep Operator Networks. Algorithms Christian Moya, Guang Lin
2022	J	`jnl`	Federated X-Armed Bandit. CoRR Wenjie Li, Qifan Song, Jean Honorio, Guang Lin
2022	Misc	`conf`	Glassoformer: A Query-Sparse Transformer for Post-Fault Power Grid Voltage Prediction. ICASSP Yunling Zheng, Carson Hu, Guang Lin, Meng Yue, Bao Wang, Jack Xin
2022	J	`jnl`	HomPINNs: Homotopy physics-informed neural networks for learning multiple solutions of nonlinear elliptic differential equations. Comput. Math. Appl. Yao Huang, Wenrui Hao, Guang Lin
2022	J	`jnl`	Implementing contact angle boundary conditions for second-order Phase-Field models of wall-bounded multiphase flows. J. Comput. Phys. Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani
2022	A*	`conf`	Interacting Contour Stochastic Gradient Langevin Dynamics. ICLR Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang
2022	J	`jnl`	Interacting Contour Stochastic Gradient Langevin Dynamics. CoRR Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang
2022	J	`jnl`	Inverse Modeling of Hydrologic Parameters in CLM4 via Generalized Polynomial Chaos in the Bayesian Framework. Comput. Georgios Karagiannis, Zhangshuan Hou, Maoyi Huang, Guang Lin
2022	J	`jnl`	Learning-PDE-Based Approximate Optimal Control for an MHD System With Uncertainty Quantification. IEEE Trans. Syst. Man Cybern. Syst. Tehuan Chen, Zhigang Ren, Guang Lin, Chao Xu
2022	J	`jnl`	Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems. CoRR Hugo Esquivel, Arun Prakash, Guang Lin
2022	J	`jnl`	Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems. J. Comput. Phys. Hugo Esquivel, Arun Prakash, Guang Lin
2022	J	`jnl`	Multi-variance replica exchange SGMCMC for inverse and forward problems via Bayesian PINN. J. Comput. Phys. Guang Lin, Yating Wang, Zecheng Zhang
2022	J	`jnl`	MultiAuto-DeepONet: A Multi-resolution Autoencoder DeepONet for Nonlinear Dimension Reduction, Uncertainty Quantification and Operator Learning of Forward and Inverse Stochastic Problems. CoRR Jiahao Zhang, Shiqi Zhang, Guang Lin
2022	J	`jnl`	NH-PINN: Neural homogenization-based physics-informed neural network for multiscale problems. J. Comput. Phys. Wing Tat Leung, Guang Lin, Zecheng Zhang
2022	J	`jnl`	Non-reversible Parallel Tempering for Deep Posterior Approximation. CoRR Wei Deng, Qian Zhang, Qi Feng, Faming Liang, Guang Lin
2022	J	`jnl`	On Learning the Dynamical Response of Nonlinear Control Systems with Deep Operator Networks. CoRR Guang Lin, Christian Moya, Zecheng Zhang
2022	J	`jnl`	PAGP: A physics-assisted Gaussian process framework with active learning for forward and inverse problems of partial differential equations. CoRR Jiahao Zhang, Shiqi Zhang, Guang Lin
2022	—	`conf`	Post-Fault Power Grid Voltage Prediction via 1D-CNN with Spatial Coupling. AI4I Carson Hu, Guang Lin, Bao Wang, Meng Yue, Jack Xin
2022	J	`jnl`	RMFGP: Rotated Multi-fidelity Gaussian process with Dimension Reduction for High-dimensional Uncertainty Quantification. CoRR Jiahao Zhang, Shiqi Zhang, Guang Lin
2022	J	`jnl`	RotEqNet: Rotation-equivariant network for fluid systems with symmetric high-order tensors. J. Comput. Phys. Liyao Gao, Yifan Du, Hongshan Li, Guang Lin
2022	J	`jnl`	Vapor-liquid equilibrium estimation of n-alkane/nitrogen mixtures using neural networks. J. Comput. Appl. Math. Suman Chakraborty, Yixuan Sun, Guang Lin, Li Qiao
2022	J	`jnl`	glassoformer: a query-sparse transformer for post-fault power grid voltage prediction. CoRR Yunling Zheng, Carson Hu, Guang Lin, Meng Yue, Bao Wang, Jack Xin
2021	J	`jnl`	A Comparative Study of Marginalized Graph Kernel and Message-Passing Neural Network. J. Chem. Inf. Model. Yan Xiang, Yu-Hang Tang, Guang Lin, Huai Sun
2021	J	`jnl`	A consistent and conservative Phase-Field model for thermo-gas-liquid-solid flows including liquid-solid phase change. CoRR Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani
2021	J	`jnl`	A consistent and conservative model and its scheme for J. Comput. Phys. Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani
2021	J	`jnl`	A consistent and conservative model and its scheme for N-phase-M-component incompressible flows. CoRR Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani
2021	J	`jnl`	A generalized multi-fidelity simulation method using sparse polynomial chaos expansion. J. Comput. Appl. Math. Jun Man, Guang Lin, Yijun Yao, Lingzao Zeng
2021	J	`jnl`	Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs. CoRR Guang Lin, Christian Moya, Zecheng Zhang
2021	A*	`conf`	Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction. ICLR Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang
2021	J	`jnl`	An adaptive Hessian approximated stochastic gradient MCMC method. J. Comput. Phys. Yating Wang, Wei Deng, Guang Lin
2021	J	`jnl`	An integrated framework for building trustworthy data-driven epidemiological models: Application to the COVID-19 outbreak in New York City. PLoS Comput. Biol. Sheng Zhang, Joan Ponce, Zhen Zhang, Guang Lin, George E. Karniadakis
2021	J	`jnl`	Bayesian sparse learning with preconditioned stochastic gradient MCMC and its applications. J. Comput. Phys. Yating Wang, Wei Deng, Guang Lin
2021	J	`jnl`	Binary classification of floor vibrations for human activity detection based on dynamic mode decomposition. Neurocomputing Shichao Zhou, Guang Lin, Qinfang Qian, Chao Xu
2021	J	`jnl`	DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks. CoRR Christian Moya, Guang Lin
2021	A	`conf`	DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving. WSDM Wei Deng, Junwei Pan, Tian Zhou, Deguang Kong, Aaron Flores, Guang Lin
2021	J	`jnl`	Feasibility of DEIM for retrieving the initial field via dimensionality reduction. J. Comput. Phys. Yuepeng Wang, Xuemei Ding, Kun Hu, Fangxin Fang, I. M. Navon, Guang Lin
2021	J	`jnl`	Flow-driven spectral chaos (FSC) method for long-time integration of second-order stochastic dynamical systems. CoRR Hugo Esquivel, Arun Prakash, Guang Lin
2021	J	`jnl`	Flow-driven spectral chaos (FSC) method for long-time integration of second-order stochastic dynamical systems. J. Comput. Appl. Math. Hugo Esquivel, Arun Prakash, Guang Lin
2021	J	`jnl`	Flow-driven spectral chaos (FSC) method for simulating long-time dynamics of arbitrary-order non-linear stochastic dynamical systems. J. Comput. Phys. Hugo Esquivel, Arun Prakash, Guang Lin
2021	J	`jnl`	Gaussian Process Assisted Active Learning of Physical Laws. Technometrics Jiuhai Chen, Lulu Kang, Guang Lin
2021	J	`jnl`	HEI: hybrid explicit-implicit learning for multiscale problems. CoRR Yalchin Efendiev, Wing Tat Leung, Guang Lin, Zecheng Zhang
2021	J	`jnl`	Identifiability and predictability of integer- and fractional-order epidemiological models using physics-informed neural networks. Nat. Comput. Sci. Ehsan Kharazmi, Min Cai, Xiaoning Zheng, Zhen Zhang, Guang Lin, George Em Karniadakis
2021	J	`jnl`	Implementing contact angle boundary conditions for second-order Phase-Field models of wall-bounded multiphase flows. CoRR Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani
2021	J	`jnl`	Multi-variance replica exchange stochastic gradient MCMC for inverse and forward Bayesian physics-informed neural network. CoRR Guang Lin, Yating Wang, Zecheng Zhang
2021	J	`jnl`	NH-PINN: Neural homogenization based physics-informed neural network for multiscale problems. CoRR Wing Tat Leung, Guang Lin, Zecheng Zhang
2021	J	`jnl`	On Convergence of Federated Averaging Langevin Dynamics. CoRR Wei Deng, Yi-An Ma, Zhao Song, Qian Zhang, Guang Lin
2021	J	`jnl`	PCNN: A physics-constrained neural network for multiphase flows. CoRR Haoyang Zheng, Ziyang Huang, Guang Lin
2021	J	`jnl`	SubTSBR to tackle high noise and outliers for data-driven discovery of differential equations. J. Comput. Phys. Sheng Zhang, Guang Lin
2021	J	`jnl`	Theoretical and numerical studies of inverse source problem for the linear parabolic equation with sparse boundary measurements. CoRR Guang Lin, Zecheng Zhang, Zhidong Zhang
2020	A*	`conf`	A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions. NeurIPS Wei Deng, Guang Lin, Faming Liang
2020	J	`jnl`	A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions. CoRR Wei Deng, Guang Lin, Faming Liang
2020	J	`jnl`	A Homotopy Method with Adaptive Basis Selection for Computing Multiple Solutions of Differential Equations. J. Sci. Comput. Wenrui Hao, Jan S. Hesthaven, Guang Lin, Bin Zheng
2020	J	`jnl`	A Low-Rank Approximated Multiscale Method for Pdes With Random Coefficients. Multiscale Model. Simul. Na Ou, Guang Lin, Lijian Jiang
2020	J	`jnl`	Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction. CoRR Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang
2020	J	`jnl`	An adaptive Hessian approximated stochastic gradient MCMC method. CoRR Yating Wang, Wei Deng, Guang Lin
2020	J	`jnl`	Bayesian Sparse learning with preconditioned stochastic gradient MCMC and its applications. CoRR Yating Wang, Wei Deng, Guang Lin
2020	J	`jnl`	Consistent and conservative scheme for incompressible two-phase flows using the conservative Allen-Cahn model. J. Comput. Phys. Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani
2020	J	`jnl`	Consistent, essentially conservative and balanced-force Phase-Field method to model incompressible two-phase flows. J. Comput. Phys. Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani
2020	J	`jnl`	DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving. CoRR Wei Deng, Junwei Pan, Tian Zhou, Aaron Flores, Guang Lin
2020	J	`jnl`	Efficient deep learning techniques for multiphase flow simulation in heterogeneous porousc media. J. Comput. Phys. Yating Wang, Guang Lin
2020	J	`jnl`	Error estimates of a spectral Petrov-Galerkin method for two-sided fractional reaction-diffusion equations. Appl. Math. Comput. Zhaopeng Hao, Guang Lin, Zhongqiang Zhang
2020	J	`jnl`	Flow-driven spectral chaos (FSC) method for simulating long-time dynamics of arbitrary-order non-linear stochastic dynamical systems. CoRR Hugo Esquivel, Arun Prakash, Guang Lin
2020	J	`jnl`	Latent transformations neural network for object view synthesis. Vis. Comput. Sangpil Kim, Nick Winovich, Hyung-Gun Chi, Guang Lin, Karthik Ramani
2020	—	`conf`	Machine-Learning-Based Online Transient Analysis via Iterative Computation of Generator Dynamics. SmartGridComm Jiaming Li, Meng Yue, Yue Zhao, Guang Lin
2020	A*	`conf`	Non-convex Learning via Replica Exchange Stochastic Gradient MCMC. ICML Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin
2020	J	`jnl`	Non-convex Learning via Replica Exchange Stochastic Gradient MCMC. CoRR Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin
2020	J	`jnl`	Real-time computational optimal control of an MHD flow system with parameter uncertainty quantification. J. Frankl. Inst. Tehuan Chen, Zhigang Ren, Guang Lin, Zongze Wu, Bao-Lin Ye
2020	J	`jnl`	Robust weighted SVD-type latent factor models for rating prediction. Expert Syst. Appl. Yiqi Gu, Xi Yang, Mengjiao Peng, Guang Lin
2019	J	`jnl`	A mixed upwind/central WENO scheme for incompressible two-phase flows. J. Comput. Phys. Ziyang Huang, Guang Lin, Arezoo Motavalizadeh Ardekani
2019	A*	`conf`	An Adaptive Empirical Bayesian Method for Sparse Deep Learning. NeurIPS Wei Deng, Xiao Zhang, Faming Liang, Guang Lin
2019	J	`jnl`	An Adaptive Empirical Bayesian Method for Sparse Deep Learning. CoRR Wei Deng, Xiao Zhang, Faming Liang, Guang Lin
2019	J	`jnl`	ConvPDE-UQ: Convolutional neural networks with quantified uncertainty for heterogeneous elliptic partial differential equations on varied domains. J. Comput. Phys. Nick Winovich, Karthik Ramani, Guang Lin
2019	J	`jnl`	Finite Element Method for Two-Sided Fractional Differential Equations with Variable Coefficients: Galerkin Approach. J. Sci. Comput. Zhaopeng Hao, Moongyu Park, Guang Lin, Zhiqiang Cai
2019	J	`jnl`	Infrared Thermal Imaging-Based Crack Detection Using Deep Learning. IEEE Access Jun Yang, Wei Wang, Guang Lin, Qing Li, Yeqing Sun, Yixuan Sun
2019	J	`jnl`	Optimal observations-based retrieval of topography in 2D shallow water equations using PC-EnKF. J. Comput. Phys. Yuepeng Wang, Kun Hu, Lanlan Ren, Guang Lin
2019	—	`conf`	Rotation-equivariant convolutional neural network ensembles in image processing. UbiComp/ISWC Adjunct Liyao Gao, Hongshan Li, Zheying Lu, Guang Lin
2019	J	`jnl`	Stochastic Security Assessment for Power Systems With High Renewable Energy Penetration Considering Frequency Regulation. IEEE Access Yu Huang, Qingshan Xu, Sajjad Abedi, Tong Zhang, Xianqiang Jiang, Guang Lin
2018	J	`jnl`	CT-GAN: Conditional Transformation Generative Adversarial Network for Image Attribute Modification. CoRR Sangpil Kim, Nick Winovich, Guang Lin, Karthik Ramani
2018	C	`conf`	Local Feature Sufficiency Exploration for Predicting Security-Constrained Generation Dispatch in Multi-area Power Systems. ICMLA Yixuan Sun, Xiaoyuan Fan, Qiuhua Huang, Xinya Li, Renke Huang, Tianzhixi Yin, Guang Lin
2018	J	`jnl`	Two-Level Spectral Methods for Nonlinear Elliptic Equations with Multiple Solutions. SIAM J. Sci. Comput. Yingwei Wang, Wenrui Hao, Guang Lin
2018	J	`jnl`	Using automatic differentiation for compressive sensing in uncertainty quantification. Optim. Methods Softw. Mu Wang, Guang Lin, Alex Pothen
2017	J	`jnl`	A high-order difference scheme for the fractional sub-diffusion equation. Int. J. Comput. Math. Zhao-peng Hao, Guang Lin, Zhi-Zhong Sun
2017	J	`jnl`	A second-order difference scheme for the time fractional substantial diffusion equation. J. Comput. Appl. Math. Zhaopeng Hao, Wanrong Cao, Guang Lin
2017	J	`jnl`	A two-level stochastic collocation method for semilinear elliptic equations with random coefficients. J. Comput. Appl. Math. Luoping Chen, Bin Zheng, Guang Lin, Nikolaos K. Voulgarakis
2017	J	`jnl`	Comparative study of clustering techniques for real-time dynamic model reduction. Stat. Anal. Data Min. Emilie Purvine, Eduardo Cotilla Sanchez, Mahantesh Halappanavar, Zhenyu Huang, Guang Lin, Shuai Lu, Shaobu Wang
2017	J	`jnl`	Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots. IEEE Trans. Vis. Comput. Graph. Junpeng Wang, Xiaotong Liu, Han-Wei Shen, Guang Lin
2017	J	`jnl`	On the Bayesian calibration of computer model mixtures through experimental data, and the design of predictive models. J. Comput. Phys. Georgios Karagiannis, Guang Lin
2017	J	`jnl`	Parallel and interacting stochastic approximation annealing algorithms for global optimisation. Stat. Comput. Georgios Karagiannis, Bledar A. Konomi, Guang Lin, Faming Liang
2017	J	`jnl`	Visualization of Time-Varying Weather Ensembles across Multiple Resolutions. IEEE Trans. Vis. Comput. Graph. Ayan Biswas, Guang Lin, Xiaotong Liu, Han-Wei Shen
2016	J	`jnl`	Classification of Spatiotemporal Data via Asynchronous Sparse Sampling: Application to Flow around a Cylinder. Multiscale Model. Simul. Ido Bright, Guang Lin, J. Nathan Kutz
2016	J	`jnl`	Enhancing sparsity of Hermite polynomial expansions by iterative rotations. J. Comput. Phys. Xiu Yang, Huan Lei, Nathan A. Baker, Guang Lin
2016	J	`jnl`	Error analysis of finite element method for Poisson-Nernst-Planck equations. J. Comput. Appl. Math. Yuzhou Sun, Pengtao Sun, Bin Zheng, Guang Lin
2016	J	`jnl`	Gaussian process surrogates for failure detection: A Bayesian experimental design approach. J. Comput. Phys. Hongqiao Wang, Guang Lin, Jinglai Li
2016	J	`jnl`	Inverse regression-based uncertainty quantification algorithms for high-dimensional models: Theory and practice. J. Comput. Phys. Weixuan Li, Guang Lin, Bing Li
2016	J	`jnl`	On Application of the Weak Galerkin Finite Element Method to a Two-Phase Model for Subsurface Flow. J. Sci. Comput. Victor Ginting, Guang Lin, Jiangguo Liu
2016	J	`jnl`	Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs. J. Comput. Phys. Qifeng Liao, Guang Lin
2016	J	`jnl`	The stabilization of BAM neural networks with time-varying delays in the leakage terms via sampled-data control. Neural Comput. Appl. Li Li, Yongqing Yang, Guang Lin
2015	J	`jnl`	A Bayesian mixed shrinkage prior procedure for spatial-stochastic basis selection and evaluation of gPC expansions: Applications to elliptic SPDEs. J. Comput. Phys. Georgios Karagiannis, Bledar A. Konomi, Guang Lin
2015	J	`jnl`	A comparative study on the weak Galerkin, discontinuous Galerkin, and mixed finite element methods. J. Comput. Appl. Math. Guang Lin, Jiangguo Liu, Farrah Sadre-Marandi
2015	J	`jnl`	A fictitious domain method with a hybrid cell model for simulating motion of cells in fluid flow. J. Comput. Phys. Wenrui Hao, Zhiliang Xu, Chun Liu, Guang Lin
2015	J	`jnl`	A frozen Gaussian approximation-based multi-level particle swarm optimization for seismic inversion. J. Comput. Phys. Jinglai Li, Guang Lin, Xu Yang
2015	J	`jnl`	An adaptive importance sampling algorithm for Bayesian inversion with multimodal distributions. J. Comput. Phys. Weixuan Li, Guang Lin
2015	J	`jnl`	Comparative Studies of Clustering Techniques for Real-Time Dynamic Model Reduction. CoRR Emilie Hogan, Eduardo Cotilla Sanchez, Mahantesh Halappanavar, Zhenyu Huang, Guang Lin, Shuai Lu, Shaobu Wang
2015	J	`jnl`	Constructing Surrogate Models of Complex Systems with Enhanced Sparsity: Quantifying the Influence of Conformational Uncertainty in Biomolecular Solvation. Multiscale Model. Simul. Huan Lei, Xiu Yang, Bin Zheng, Guang Lin, Nathan A. Baker
2015	J	`jnl`	Full scale multi-output Gaussian process emulator with nonseparable auto-covariance functions. J. Comput. Phys. Bohai Zhang, Bledar A. Konomi, Huiyan Sang, Georgios Karagiannis, Guang Lin
2014	J	`jnl`	An adaptive ANOVA-based PCKF for high-dimensional nonlinear inverse modeling. J. Comput. Phys. Weixuan Li, Guang Lin, Dongxiao Zhang
2014	J	`jnl`	Bayesian Treed Multivariate Gaussian Process With Adaptive Design: Application to a Carbon Capture Unit. Technometrics Bledar A. Konomi, Georgios Karagiannis, Avik Sarkar, Xin Sun, Guang Lin
2014	J	`jnl`	Rare-Event Simulation for the Stochastic Korteweg-de Vries Equation. SIAM/ASA J. Uncertain. Quantification Gongjun Xu, Guang Lin, Jingchen Liu
2014	J	`jnl`	Selection of polynomial chaos bases via Bayesian model uncertainty methods with applications to sparse approximation of PDEs with stochastic inputs. J. Comput. Phys. Georgios Karagiannis, Guang Lin
2014	J	`jnl`	Weak Galerkin finite element methods for Darcy flow: Anisotropy and heterogeneity. J. Comput. Phys. Guang Lin, Jiangguo Liu, Lin Mu, Xiu Ye
2013	J	`jnl`	Evaluating the impact of aquifer layer properties on geomechanical response during CO Comput. Geosci. Jie Bao, Zhijie Xu, Guang Lin, Yilin Fang
2013	B	`conf`	Exploring Cloud Computing for Large-Scale Scientific Applications. SERVICES Guang Lin, Binh Han, Jian Yin, Ian Gorton
2013	J	`jnl`	Hybrid parallel computing of minimum action method. Parallel Comput. Xiaoliang Wan, Guang Lin
2013	J	`jnl`	Multi-output separable Gaussian process: Towards an efficient, fully Bayesian paradigm for uncertainty quantification. J. Comput. Phys. Ilias Bilionis, Nicholas Zabaras, Bledar A. Konomi, Guang Lin
2013	J	`jnl`	Numerical solution of the Stratonovich- and Ito-Euler equations: Application to the stochastic piston problem. J. Comput. Phys. Zhongqiang Zhang, Xiu Yang, Guang Lin, George E. Karniadakis
2012	J	`jnl`	Adaptive ANOVA decomposition of stochastic incompressible and compressible flows. J. Comput. Phys. Xiu Yang, Minseok Choi, Guang Lin, George E. Karniadakis
2011	Misc	`conf`	MeDiCi-Cloud: A Workflow Infrastructure for Large-scale Scientific Applications. UCC Jian Yin, Guang Lin, Ian Gorton, Binh Han
2011	J	`jnl`	Point-wise hierarchical reconstruction for discontinuous Galerkin and finite volume methods for solving conservation laws. J. Comput. Phys. Zhiliang Xu, Yingjie Liu, Huijing Du, Guang Lin, Chi-Wang Shu
2010	J	`jnl`	Numerical Studies of Three-dimensional Stochastic Darcy's Equation and Stochastic Advection-Diffusion-Dispersion Equation. J. Sci. Comput. Guang Lin, Alexandre M. Tartakovsky
2010	J	`jnl`	Uncertainty quantification via random domain decomposition and probabilistic collocation on sparse grids. J. Comput. Phys. Guang Lin, Alexandre M. Tartakovsky, Daniel M. Tartakovsky
2007	J	`jnl`	Stochastic Computational Fluid Mechanics. Comput. Sci. Eng. Guang Lin, Xiaoliang Wan, Chau-Hsing Su, George E. Karniadakis
2006	J	`jnl`	Numerical studies of the stochastic Korteweg-de Vries equation. J. Comput. Phys. Guang Lin, Leopold Grinberg, George E. Karniadakis
2006	J	`jnl`	Predicting shock dynamics in the presence of uncertainties. J. Comput. Phys. Guang Lin, Chau-Hsing Su, George E. Karniadakis