Liang Yan

Orcid: 0000-0002-4515-9125

Affiliations:
  • Southeast University, Department of Mathematics, Nanjing, China
  • Lanzhou University, School of Mathematics and Statistics, China (former)


According to our database1, Liang Yan authored at least 25 papers between 2009 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of five.

Timeline

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Bibliography

2025
Physics-Aware Deep Learning Framework for the Limited Aperture Inverse Obstacle Scattering Problem.
SIAM J. Sci. Comput., 2025

TDDM: A transfer learning framework for physics-guided 3D acoustic scattering inversion.
J. Comput. Phys., 2025

Deep learning-enhanced reduced-order ensemble Kalman filter for efficient Bayesian data assimilation of parametric PDEs.
Comput. Phys. Commun., 2025

2024
Inverse elastic scattering by random periodic structures.
J. Comput. Phys., March, 2024

Adaptive Operator Learning for Infinite-Dimensional Bayesian Inverse Problems.
SIAM/ASA J. Uncertain. Quantification, 2024

2023
Failure-Informed Adaptive Sampling for PINNs.
SIAM J. Sci. Comput., August, 2023

Surrogate modeling for Bayesian inverse problems based on physics-informed neural networks.
J. Comput. Phys., February, 2023

Failure-informed adaptive sampling for PINNs, Part II: combining with re-sampling and subset simulation.
CoRR, 2023

2021
Optimal design for kernel interpolation: Applications to uncertainty quantification.
J. Comput. Phys., 2021

An acceleration strategy for randomize-then-optimize sampling via deep neural networks.
CoRR, 2021

Stein variational gradient descent with local approximations.
CoRR, 2021

Gradient-free Stein variational gradient descent with kernel approximation.
Appl. Math. Lett., 2021

2019
Adaptive multi-fidelity polynomial chaos approach to Bayesian inference in inverse problems.
J. Comput. Phys., 2019

An adaptive surrogate modeling based on deep neural networks for large-scale Bayesian inverse problems.
CoRR, 2019

2018
Weighted Approximate Fekete Points: Sampling for Least-Squares Polynomial Approximation.
SIAM J. Sci. Comput., 2018

Doubly stochastic radial basis function methods.
J. Comput. Phys., 2018

2017
Sparse Approximation using ℓ<sub>1-ℓ<sub>2</sub></sub> Minimization and Its Application to Stochastic Collocation.
SIAM J. Sci. Comput., 2017

2015
Stochastic Collocation Algorithms Using l<sub>1</sub>-Minimization for Bayesian Solution of Inverse Problems.
SIAM J. Sci. Comput., 2015

The method of approximate particular solutions for the time-fractional diffusion equation with a non-local boundary condition.
Comput. Math. Appl., 2015

2014
Efficient Kansa-type MFS algorithm for time-fractional inverse diffusion problems.
Comput. Math. Appl., 2014

2013
On the interface identification of free boundary problem by method of fundamental solution.
Numer. Linear Algebra Appl., 2013

2011
Approximate inverse method for stable analytic continuation in a strip domain.
J. Comput. Appl. Math., 2011

2009
Reconstruction of the corrosion boundary for the Laplace equation by using a boundary collocation method.
Math. Comput. Simul., 2009

A meshless method for solving an inverse spacewise-dependent heat source problem.
J. Comput. Phys., 2009

A Bayesian inference approach to identify a Robin coefficient in one-dimensional parabolic problems.
J. Comput. Appl. Math., 2009


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