Jinglai Li
Orcid: 0000-0001-7980-6901
According to our database1,
Jinglai Li
authored at least 34 papers
between 2011 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on zbmath.org
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on orcid.org
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on github.com
On csauthors.net:
Bibliography
2024
Reliab. Eng. Syst. Saf., January, 2024
On Estimating the Gradient of the Expected Information Gain in Bayesian Experimental Design.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
VI-DGP: A Variational Inference Method with Deep Generative Prior for Solving High-Dimensional Inverse Problems.
J. Sci. Comput., October, 2023
Reliab. Eng. Syst. Saf., September, 2023
On multilevel Monte Carlo methods for deterministic and uncertain hyperbolic systems.
J. Comput. Phys., February, 2023
Deep Unrolling Networks with Recurrent Momentum Acceleration for Nonlinear Inverse Problems.
CoRR, 2023
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems.
CoRR, 2023
Approximate Primal-Dual Fixed-Point based Langevin Algorithms for Non-smooth Convex Potentials.
CoRR, 2023
2022
Ensemble Kalman filter based sequential Monte Carlo sampler for sequential Bayesian inference.
Stat. Comput., 2022
Clustered active-subspace based local Gaussian Process emulator for high-dimensional and complex computer models.
J. Comput. Phys., 2022
CoRR, 2022
CoRR, 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
SIAM J. Sci. Comput., 2021
2020
Bayesian Inference and Uncertainty Quantification for Medical Image Reconstruction with Poisson Data.
SIAM J. Imaging Sci., 2020
SIAM/ASA J. Uncertain. Quantification, 2020
Proceedings of the Machine Learning, Optimization, and Data Science, 2020
An approximate KLD based experimental design for models with intractable likelihoods.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
An adaptive reduced basis ANOVA method for high-dimensional Bayesian inverse problems.
J. Comput. Phys., 2019
IEEE Access, 2019
2018
An Adaptive Independence Sampler MCMC Algorithm for Bayesian Inferences of Functions.
SIAM J. Sci. Comput., 2018
Adaptive Gaussian Process Approximation for Bayesian Inference with Expensive Likelihood Functions.
Neural Comput., 2018
2017
SIAM/ASA J. Uncertain. Quantification, 2017
On an adaptive preconditioned Crank-Nicolson MCMC algorithm for infinite dimensional Bayesian inference.
J. Comput. Phys., 2017
J. Comput. Phys., 2017
2016
A surrogate accelerated multicanonical Monte Carlo method for uncertainty quantification.
J. Comput. Phys., 2016
Gaussian process surrogates for failure detection: A Bayesian experimental design approach.
J. Comput. Phys., 2016
2015
A frozen Gaussian approximation-based multi-level particle swarm optimization for seismic inversion.
J. Comput. Phys., 2015
2014
SIAM J. Sci. Comput., 2014
2012
2011
J. Comput. Phys., 2011