9 papers
Bayesian Inference for PDE-based Inverse Problems using the Optimization of a Discrete Loss
Lucas Amoudruz, Sergey Litvinov, Costas Papadimitriou +1
Inverse problems are crucial for many applications in science, engineering and medicine that involve data assimilation, design, and imaging. Their solution infers the parameters or…
Prediction of Extreme Events in Multiscale Simulations of Geophysical Turbulence using Reinforcement Learning
Yifei Guan, Lucas Amoudruz, Sergey Litvinov +4
Accurate subgrid-scale closures are essential for weather/climate models, where predicting extreme events is critical. Traditional closures have structural errors, e.g., producing…
Scalable, Cloud-Based Simulations of Blood Flow and Targeted Drug Delivery in Retinal Capillaries
Lucas Amoudruz, Sergey Litvinov, Riccardo Murri +4
We investigate the capabilities of cloud computing for large-scale,tightly-coupled simulations of biological fluids in complex geometries, traditionally performed in supercomputing…
Individualizing Glioma Radiotherapy Planning by Optimization of Data and Physics-Informed Discrete Loss
Michal Balcerak, Jonas Weidner, Petr Karnakov +8
Brain tumor growth is unique to each glioma patient and extends beyond what is visible in imaging scans, infiltrating surrounding brain tissue. Understanding these hidden patient-s…
Data-Driven Discovery of Interpretable Kalman Filter Variants through Large Language Models and Genetic Programming
Vasileios Saketos, Sebastian Kaltenbach, Sergey Litvinov +1
Algorithmic discovery has traditionally relied on human ingenuity and extensive experimentation. Here we investigate whether a prominent scientific computing algorithm, the Kalman…
Inertial Focusing of Spherical Particles: The Effects of Rotational Motion
Dmitry Alexeev, Sergey Litvinov, Athena Economides +3
The identification of cells and particles based on their transport properties in microfluidic devices is crucial for numerous applications in biology and medicine. Neutrally buoyan…