The method of fundamental solutions for the inverse heat source problem L Yan, CL Fu, FL Yang
Engineering Analysis with Boundary Elements 32 (3), 216-222, 2008
244 2008 Stochastic Collocation Algorithms using l1--Minimization L Yan, L Guo, D Xiu
International Journal for Uncertainty Quantification 2 (3), 279-293, 2012
151 2012 A meshless method for solving an inverse spacewise-dependent heat source problem L Yan, FL Yang, CL Fu
Journal of Computational Physics 228 (1), 123-136, 2009
130 2009 Adaptive multi-fidelity polynomial chaos approach to Bayesian inference in inverse problems L Yan, T Zhou
Journal of Computational Physics 381, 110-128, 2019
116 2019 Failure-informed adaptive sampling for PINNs Z Gao, L Yan, T Zhou
SIAM Journal on Scientific Computing 45 (4), A1971-A1994, 2023
99 2023 An adaptive surrogate modeling based on deep neural networks for large-scale Bayesian inverse problems L Yan, T Zhou
Communications in Computational Physics 28, 2180-2205, 2020
61 2020 Sparse Approximation using L Yan, Y Shin, D Xiu
SIAM Journal on Scientific Computing 39 (1), A229-A254, 2017
54 2017 A computational method for identifying a spacewise‐dependent heat source L Yan, CL Fu, FF Dou
International Journal for Numerical Methods in Biomedical Engineering 26 (5 …, 2010
53 2010 Weighted approximate Fekete points: sampling for least-squares polynomial approximation L Guo, A Narayan, L Yan, T Zhou
SIAM Journal on Scientific Computing 40 (1), A366-A387, 2018
35 2018 Stochastic collocation algorithms using l1-minimization for Bayesian solution of inverse problems L Yan, L Guo.
SIAM Journal on Scientific Computing 37 (3), A1410–A1435, 2015
35 2015 The method of approximate particular solutions for the time-fractional diffusion equation with a non-local boundary condition L Yan, FL Yang.
Computers and Mathematics with Applications 70 (3), 254-264, 2015
30 2015 Convergence analysis of surrogate-based methods for Bayesian inverse problems L Yan, YX Zhang
Inverse Problems 33 (12), 125001, 2017
29 2017 On the uniqueness and reconstruction for an inverse problem of the fractional diffusion process JJ Liu, M Yamamoto, L Yan.
Applied Numerical Mathematics 87, 1-19, 2015
29 2015 The identification of a Robin coefficient by a conjugate gradient method F Yang, L Yan, T Wei
International journal for numerical methods in engineering 78 (7), 800-816, 2009
29 2009 A Bayesian inference approach to identify a Robin coefficient in one-dimensional parabolic problems L Yan, F Yang, C Fu
Journal of Computational and Applied Mathematics 231 (2), 840-850, 2009
28 2009 On the reconstruction of unknown time-dependent boundary sources for time fractional diffusion process by distributing measurement JJ Liu, M Yamamoto, L Yan
Inverse Problems 32, 015009 (25pp), 2016
25 2016 Bayesian approach to a nonlinear inverse problem for time-space fractional diffusion equation YX Zhang, J Jia, L Yan
Inverse Problems 34, 125002, 2018
24 2018 Doubly stochastic radial basis function methods F Yang, L Yan, L Ling
Journal of Computational Physics 363, 87-97, 2018
24 2018 An adaptive multifidelity PC-based ensemble Kalman inversion for inverse problems L Yan, T Zhou
International Journal for Uncertainty Quantification 9 (3), 205-220, 2019
23 2019 Surrogate modeling for Bayesian inverse problems based on physics-informed neural networks Y Li, Y Wang, L Yan
Journal of Computational Physics 475, 111841, 2023
21 2023 
Tao ZhouProfessor of Mathematics, Chinese Academy of SciencesAdresse e-mail validée de lsec.cc.ac.cn