Modulus-based iterative methods for constrained ℓp–ℓq minimization A Buccini, M Pasha, L Reichel Inverse Problems 36 (8), 084001, 2020 | 28 | 2020 |
Generalized singular value decomposition with iterated Tikhonov regularization A Buccini, M Pasha, L Reichel Journal of Computational and Applied Mathematics 373, 112276, 2020 | 28 | 2020 |
Randomized algorithms for rounding in the tensor-train format H Al Daas, G Ballard, P Cazeaux, E Hallman, A Międlar, M Pasha, ... SIAM Journal on Scientific Computing 45 (1), A74-A95, 2023 | 19 | 2023 |
Linearized Krylov subspace Bregman iteration with nonnegativity constraint A Buccini, M Pasha, L Reichel Numerical Algorithms 87, 1177-1200, 2021 | 13 | 2021 |
Optimal transport for parameter identification of chaotic dynamics via invariant measures Y Yang, L Nurbekyan, E Negrini, R Martin, M Pasha SIAM Journal on Applied Dynamical Systems 22 (1), 269-310, 2023 | 12 | 2023 |
Efficient learning methods for large-scale optimal inversion design J Chung, M Chung, S Gazzola, M Pasha arXiv preprint arXiv:2110.02720, 2021 | 6 | 2021 |
Bayesian spatiotemporal modeling for inverse problems S Lan, S Li, M Pasha Statistics and Computing 33 (4), 89, 2023 | 5 | 2023 |
A computational framework for edge-preserving regularization in dynamic inverse problems M Pasha, AK Saibaba, S Gazzola, MI Español, E de Sturler Electronic Transactions on Numerical Analysis 58, 486-516, 2023 | 5* | 2023 |
Variable projection methods for separable nonlinear inverse problems with general-form Tikhonov regularization MI Español, M Pasha Inverse Problems 39 (8), 084002, 2023 | 3 | 2023 |
A Krylov subspace type method for Electrical Impedance Tomography M Pasha, S Kupis, S Ahmad, T Khan ESAIM: Mathematical Modelling and Numerical Analysis 55 (6), 2827-2847, 2021 | 3 | 2021 |
The Image Deblurring Problem: Matrices, Wavelets, and Multilevel Methods D Austin, MI Español, M Pasha Notices of the American Mathematical Society 69 (8), 2022 | 2 | 2022 |
Krylov subspace type methods for the computation of non-negative or sparse solutions of ill-posed problems M Pasha Kent State University, 2020 | 2 | 2020 |
Tensor Completion with BMD factor nuclear norm minimization F Tian, M Pasha, M Kilmer, E Miller, A Patra http://arxiv.org/abs/2402.13068, 2024 | 1 | 2024 |
Spatiotemporal Besov priors for Bayesian inverse problems S Lan, M Pasha, S Li arXiv preprint arXiv:2306.16378, 2023 | 1 | 2023 |
Efficient learning methods for large-scale optimal inversion design M Pasha, J Chung, M Chung, S Gazzola 2022 virtual joint mathematics meetings (JMM 2022), 2022 | 1 | 2022 |
An Variable Projection Method for Large-Scale Separable Nonlinear Inverse Problems M Espanol, M Pasha arXiv preprint arXiv:2105.14155, 2021 | 1 | 2021 |
TRIPs-Py: Techniques for Regularization of Inverse Problems in Python M Pasha, S Gazzola, C Sanderford, U Ugwu https://arxiv.org/pdf/2402.17603.pdf, 2024 | | 2024 |
Recycling MMGKS for large-scale dynamic and streaming data M Pasha, E de Sturler, M Kilmer https://arxiv.org/abs/2309.15759, 2023 | | 2023 |
Sparse representation learning derives biological features with explicit gene weights from the Allen Mouse Brain Atlas M Abbasi, CR Sanderford, N Raghu, M Pasha, BB Bartelle PloS one 18 (3), e0282171, 2023 | | 2023 |
Computationally Efficient Methods for Large-Scale Inverse Problems: From Learning to Sparsity and Edge-Preserving M Pasha | | 2022 |