A Learnable Prior Improves Inverse Tumor Growth Modeling. - Weidner, Jonas; Ezhov, Ivan; Balcerak, Michal; Metz, Marie-Christin; Litvinov, Sergey; Kaltenbach, Sebastian; Feiner, Leonhard F.; Lux, Laurin; Kofler, Florian; Lipková, Jana; Latz, Jonas; Rueckert, Daniel; et al. (IEEE Trans. Medical Imaging, 2025)

Optimal Lattice Boltzmann Closures through Multi-Agent Reinforcement Learning. - Fischer, Paul; Kaltenbach, Sebastian; Litvinov, Sergey; Succi, Sauro; Koumoutsakos, Petros (CoRR, 2025)

A Learnable Prior Improves Inverse Tumor Growth Modeling. - Weidner, Jonas; Ezhov, Ivan; Balcerak, Michal; Metz, Marie-Christin; Litvinov, Sergey; Kaltenbach, Sebastian; Feiner, Leonhard F.; Lux, Laurin; Kofler, Florian; Lipková, Jana; Latz, Jonas; Rueckert, Daniel; et al. (CoRR, 2024)

Path planning of magnetic microswimmers in high-fidelity simulations of capillaries with deep reinforcement learning. - Amoudruz, Lucas; Litvinov, Sergey; Koumoutsakos, Petros (CoRR, 2024)

Flow reconstruction by multiresolution optimization of a discrete loss with automatic differentiation. - Karnakov, Petr; Litvinov, Sergey; Koumoutsakos, Petros (CoRR, 2023)

Individualizing Glioma Radiotherapy Planning by Optimization of a Data and Physics Informed Discrete Loss. - Balcerak, Michal; Ezhov, Ivan; Karnakov, Petr; Litvinov, Sergey; Koumoutsakos, Petros; Weidner, Jonas; Zhang, Ray Zirui; Lowengrub, John S.; Wiestler, Benedikt; Menze, Bjoern H. (CoRR, 2023)

Optimizing a DIscrete Loss (ODIL) to solve forward and inverse problems for partial differential equations using machine learning tools. - Karnakov, Petr; Litvinov, Sergey; Koumoutsakos, Petros (CoRR, 2022)

Computing foaming flows across scales: from breaking waves to microfluidics. - Karnakov, Petr; Litvinov, Sergey; Koumoutsakos, Petros (CoRR, 2021)

Mirheo: High-performance mesoscale simulations for microfluidics. - Alexeev, Dmitry; Amoudruz, Lucas; Litvinov, Sergey; Koumoutsakos, Petros (Comput. Phys. Commun., 2020)

Aphros: High Performance Software for Multiphase Flows with Large Scale Bubble and Drop Clusters. - Karnakov, Petr; Wermelinger, Fabian; Litvinov, Sergey; Koumoutsakos, Petros (2020)

A High Performance Computing Framework for Multiphase, Turbulent Flows on Structured Grids. - Karnakov, Petr; Wermelinger, Fabian; Chatzimanolakis, Michail; Litvinov, Sergey; Koumoutsakos, Petros (2019)

Bending models of lipid bilayer membranes: spontaneous curvature and area-difference elasticity. - Bian, Xin; Litvinov, Sergey; Koumoutsakos, Petros (CoRR, 2019)

A hybrid particle volume-of-fluid method for curvature estimation in multiphase flows. - Karnakov, Petr; Litvinov, Sergey; Koumoutsakos, Petros (CoRR, 2019)

Mirheo: High-Performance Mesoscale Simulations for Microfluidics. - Alexeev, Dmitry; Amoudruz, Lucas; Litvinov, Sergey; Koumoutsakos, Petros (CoRR, 2019)

A novel partitioning method for block-structured adaptive meshes. - Fu, Lin; Litvinov, Sergey; Hu, Xiangyu; Adams, Nikolaus A. (J. Comput. Phys., 2017)

Towards the Virtual Rheometer: High Performance Computing for the Red Blood Cell Microstructure. - Economides, Athena; Amoudruz, Lucas; Litvinov, Sergey; Alexeev, Dmitry; Nizzero, Sara; Hadjidoukas, Panagiotis E.; Rossinelli, Diego; Koumoutsakos, Petros (2017)

Numerical methods for the weakly compressible Generalized Langevin Model in Eulerian reference frame. - Azarnykh, Dmitrii; Litvinov, Sergey; Adams, Nikolaus A. (J. Comput. Phys., 2016)

Towards consistence and convergence of conservative SPH approximations. - Litvinov, Sergey; Hu, Xiangyu; Adams, Nikolaus A. (J. Comput. Phys., 2015)

A splitting scheme for highly dissipative smoothed particle dynamics. - Litvinov, Sergey; Ellero, Marco; Hu, Xiangyu; Adams, Nikolaus A. (J. Comput. Phys., 2010)