| A mixed elasticity formulation for fluid-poroelastic structure interaction T Li, I Yotov ESAIM: Mathematical Modelling and Numerical Analysis (M2AN) 56, 1-40, 2020 | 29 | 2020 |
| A multipoint stress-flux mixed finite element method for the Stokes-Biot model S Caucao, T Li, I Yotov Numerische Mathematik, 2022 | 22 | 2022 |
| An augmented fully mixed formulation for the quasistatic Navier–Stokes–Biot model T Li, S Caucao, I Yotov IMA Journal of Numerical Analysis 44 (2), 1153-1210, 2024 | 8 | 2024 |
| A cell-centered finite volume method for the Navier–Stokes/Biot model S Caucao, T Li, I Yotov Finite Volumes for Complex Applications IX-Methods, Theoretical Aspects …, 2020 | 4 | 2020 |
| Improving numerical accuracy for the viscous-plastic formulation of sea ice T Li, A Gelb, Y Lee Journal of Computational Physics 487, 112184, 2023 | 2 | 2023 |
| Non-Newtonian and poroelastic effects in simulations of arterial flows T Li, X Wang, I Yotov arXiv preprint arXiv:2010.14072, 2020 | 2 | 2020 |
| Entropy stable conservative flux form neural networks L Liu, T Li, A Gelb, Y Lee arXiv preprint arXiv:2411.01746, 2024 | 1 | 2024 |
| Mixed formulations for fluid-poroelastic structure interaction T Li University of Pittsburgh, 2021 | 1 | 2021 |
| A Bayesian framework for spectral reprojection T Li, A Gelb Journal of Scientific Computing 102 (3), 1-28, 2025 | | 2025 |
| A structurally informed data assimilation approach for nonlinear partial differential equations T Li, A Gelb, Y Lee Journal of Computational Physics 519, 113396, 2024 | | 2024 |
| Mixed Finite Element Methods for the Navier–Stokes–Biot Model S Caucao, A Dalal, T Li, I Yotov International Conference on Large-Scale Scientific Computing, 19-31, 2023 | | 2023 |
| Using Bayesian spectral reprojection to resolve the Gibbs phenomenon T Li, A Gelb | | |
Ivan YotovUniversity of PittsburghVerifisert e-postadresse på math.pitt.edu
