Jinglai Li - RankMe

52 papers A* 2A 3Journal 46Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A New Convergence Analysis of Plug-and-Play Proximal Gradient Descent Under Prior Mismatch. CoRR Guixian Xu, Jinglai Li, Junqi Tang
2026	J	`jnl`	The Practicality of Normalizing Flow Test-Time Training in Bayesian Inference for Agent-Based Models. CoRR Junyao Zhang, Jinglai Li, Junqi Tang
2025	J	`jnl`	A neural-network based nonlinear non-intrusive reduced basis method with online adaptation for parametrized partial differential equations. CoRR Jingye Li, Alex Bespalov, Jinglai Li
2025	A	`conf`	Bayesian Optimization for CVaR-based portfolio optimization. GECCO Robert Millar, Jinglai Li
2025	J	`jnl`	Fast Equivariant Imaging: Acceleration for Unsupervised Learning via Augmented Lagrangian and Auxiliary PnP Denoisers. CoRR Guixian Xu, Jinglai Li, Junqi Tang
2025	J	`jnl`	Gaussian Processes Regression for Uncertainty Quantification: An Introductory Tutorial. CoRR Jinglai Li, Hongqiao Wang
2025	J	`jnl`	Stochastic gradient descent based variational inference for infinite-dimensional inverse problems. CoRR Jiaming Sui, Junxiong Jia, Jinglai Li
2024	J	`jnl`	Domain-decomposed Bayesian inversion based on local Karhunen-Loève expansions. J. Comput. Phys. Zhihang Xu, Qifeng Liao, Jinglai Li
2024	J	`jnl`	NF-ULA: Normalizing Flow-Based Unadjusted Langevin Algorithm for Imaging Inverse Problems. SIAM J. Imaging Sci. Ziruo Cai, Junqi Tang, Subhadip Mukherjee, Jinglai Li, Carola-Bibiane Schönlieb, Xiaoqun Zhang
2024	A	`conf`	ODEs Learn to Walk: ODE-Net based Data-Driven Modeling for Crowd Dynamics. AAMAS Chen Cheng, Jinglai Li
2024	A*	`conf`	On Estimating the Gradient of the Expected Information Gain in Bayesian Experimental Design. AAAI Ziqiao Ao, Jinglai Li
2024	J	`jnl`	Sampling-based adaptive design strategy for failure probability estimation. Reliab. Eng. Syst. Saf. Tiexin Guo, Hongji Wang, Jinglai Li, Hongqiao Wang
2024	J	`jnl`	Sketched Equivariant Imaging Regularization and Deep Internal Learning for Inverse Problems. CoRR Guixian Xu, Jinglai Li, Junqi Tang
2023	J	`jnl`	Approximate Primal-Dual Fixed-Point based Langevin Algorithms for Non-smooth Convex Potentials. CoRR Ziruo Cai, Jinglai Li, Xiaoqun Zhang
2023	J	`jnl`	Deep Unrolling Networks with Recurrent Momentum Acceleration for Nonlinear Inverse Problems. CoRR Qingping Zhou, Jiayu Qian, Junqi Tang, Jinglai Li
2023	J	`jnl`	Entropy Estimation via Uniformization. CoRR Ziqiao Ao, Jinglai Li
2023	J	`jnl`	Entropy estimation via uniformization. Artif. Intell. Ziqiao Ao, Jinglai Li
2023	J	`jnl`	Multicanonical sequential Monte Carlo sampler for uncertainty quantification. Reliab. Eng. Syst. Saf. Robert Millar, Hui Li, Jinglai Li
2023	J	`jnl`	NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems. CoRR Ziruo Cai, Junqi Tang, Subhadip Mukherjee, Jinglai Li, Carola-Bibiane Schönlieb, Xiaoqun Zhang
2023	J	`jnl`	On Estimating the Gradient of the Expected Information Gain in Bayesian Experimental Design. CoRR Ziqiao Ao, Jinglai Li
2023	J	`jnl`	On multilevel Monte Carlo methods for deterministic and uncertain hyperbolic systems. J. Comput. Phys. Junpeng Hu, Shi Jin, Jinglai Li, Lei Zhang
2023	J	`jnl`	VI-DGP: A Variational Inference Method with Deep Generative Prior for Solving High-Dimensional Inverse Problems. J. Sci. Comput. Yingzhi Xia, Qifeng Liao, Jinglai Li
2023	J	`jnl`	VI-DGP: A variational inference method with deep generative prior for solving high-dimensional inverse problems. CoRR Yingzhi Xia, Qifeng Liao, Jinglai Li
2022	J	`jnl`	Affine-mapping based variational ensemble Kalman filter. Stat. Comput. Linjie Wen, Jinglai Li
2022	J	`jnl`	Clustered active-subspace based local Gaussian Process emulator for high-dimensional and complex computer models. J. Comput. Phys. Junda Xiong, Xin Cai, Jinglai Li
2022	J	`jnl`	Domain-decomposed Bayesian inversion based on local Karhunen-Loève expansions. CoRR Zhihang Xu, Qifeng Liao, Jinglai Li
2022	J	`jnl`	Ensemble Kalman filter based sequential Monte Carlo sampler for sequential Bayesian inference. Stat. Comput. Jiangqi Wu, Linjie Wen, Peter L. Green, Jinglai Li, Simon Maskell
2022	A*	`conf`	Entropy Estimation via Normalizing Flow. AAAI Ziqiao Ao, Jinglai Li
2022	J	`jnl`	ODEs learn to walk: ODE-Net based data-driven modeling for crowd dynamics. CoRR Chen Cheng, Jinglai Li
2022	J	`jnl`	On multilevel Monte Carlo methods for deterministic and uncertain hyperbolic systems. CoRR Junpeng Hu, Shi Jin, Jinglai Li, Lei Zhang
2021	J	`jnl`	Clustered active-subspace based local Gaussian Process emulator for high-dimensional and complex computer models. CoRR Junda Xiong, Xin Cai, Jinglai Li
2021	J	`jnl`	Linear-Mapping based Variational Ensemble Kalman Filter. CoRR Linjie Wen, Jinglai Li
2021	J	`jnl`	Maximum Conditional Entropy Hamiltonian Monte Carlo Sampler. SIAM J. Sci. Comput. Tengchao Yu, Hongqiao Wang, Jinglai Li
2020	J	`jnl`	A Defensive Marginal Particle Filtering Method for Data Assimilation. SIAM/ASA J. Uncertain. Quantification Linjie Wen, Jiangqi Wu, Linjun Lu, Jinglai Li
2020	A	`conf`	An approximate KLD based experimental design for models with intractable likelihoods. AISTATS Ziqiao Ao, Jinglai Li
2020	J	`jnl`	Bayesian Inference and Uncertainty Quantification for Medical Image Reconstruction with Poisson Data. SIAM J. Imaging Sci. Qingping Zhou, Tengchao Yu, Xiaoqun Zhang, Jinglai Li
2020	—	`conf`	Bayesian Optimization with Local Search. LOD (2) Yuzhou Gao, Tengchao Yu, Jinglai Li
2019	J	`jnl`	A Hierarchical Neural Hybrid Method for Failure Probability Estimation. IEEE Access Ke Li, Kejun Tang, Jinglai Li, Tianfan Wu, Qifeng Liao
2019	J	`jnl`	A hierarchical neural hybrid method for failure probability estimation. CoRR Ke Li, Kejun Tang, Jinglai Li, Tianfan Wu, Qifeng Liao
2019	J	`jnl`	An adaptive reduced basis ANOVA method for high-dimensional Bayesian inverse problems. J. Comput. Phys. Qifeng Liao, Jinglai Li
2019	J	`jnl`	Bayesian optimization with local search. CoRR Yuzhou Gao, Tengchao Yu, Jinglai Li
2018	J	`jnl`	Adaptive Gaussian Process Approximation for Bayesian Inference with Expensive Likelihood Functions. Neural Comput. Hongqiao Wang, Jinglai Li
2018	J	`jnl`	An Adaptive Independence Sampler MCMC Algorithm for Bayesian Inferences of Functions. SIAM J. Sci. Comput. Zhe Feng, Jinglai Li
2017	J	`jnl`	A Hybrid Adaptive MCMC Algorithm in Function Spaces. SIAM/ASA J. Uncertain. Quantification Qingping Zhou, Zixi Hu, Zhewei Yao, Jinglai Li
2017	J	`jnl`	A subset multicanonical Monte Carlo method for simulating rare failure events. J. Comput. Phys. Xinjuan Chen, Jinglai Li
2017	J	`jnl`	On an adaptive preconditioned Crank-Nicolson MCMC algorithm for infinite dimensional Bayesian inference. J. Comput. Phys. Zixi Hu, Zhewei Yao, Jinglai Li
2016	J	`jnl`	A surrogate accelerated multicanonical Monte Carlo method for uncertainty quantification. J. Comput. Phys. Keyi Wu, Jinglai Li
2016	J	`jnl`	Gaussian process surrogates for failure detection: A Bayesian experimental design approach. J. Comput. Phys. Hongqiao Wang, Guang Lin, Jinglai Li
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
2014	J	`jnl`	Adaptive Construction of Surrogates for the Bayesian Solution of Inverse Problems. SIAM J. Sci. Comput. Jinglai Li, Youssef M. Marzouk
2012	J	`jnl`	Extracting Solitons from Noisy Pulses. SIAM J. Appl. Math. Jinglai Li, William L. Kath
2011	J	`jnl`	An efficient surrogate-based method for computing rare failure probability. J. Comput. Phys. Jing Li, Jinglai Li, Dongbin Xiu