23 citations · 30 across the 8 of their papers we have counts for
8 papers
STFlow: Data-Coupled Flow Matching for Geometric Trajectory Simulation
Kiet Bennema ten Brinke, Koen Minartz, Vlado Menkovski
Simulating trajectories of dynamical systems is a fundamental problem in a wide range of fields such as molecular dynamics, biochemistry, and pedestrian dynamics. Machine learning…
Deep Neural Cellular Potts Models
Koen Minartz, Tim d'Hondt, Leon Hillmann +3
The cellular Potts model (CPM) is a powerful computational method for simulating collective spatiotemporal dynamics of biological cells. To drive the dynamics, CPMs rely on physics…
Understanding complex crowd dynamics with generative neural simulators
Koen Minartz, Fleur Hendriks, Simon Martinus Koop +2
Understanding the dynamics of pedestrian crowds is an outstanding challenge crucial for designing efficient urban infrastructure and ensuring safe crowd management. To this end, bo…
Efficient Probabilistic Modeling of Crystallization at Mesoscopic Scale
Pol Timmer, Koen Minartz, Vlado Menkovski
Crystallization processes at the mesoscopic scale, where faceted, dendritic growth, and multigrain formation can be observed, are of particular interest within materials science an…
Accelerating Simulation of Two-Phase Flows with Neural PDE Surrogates
Yoeri Poels, Koen Minartz, Harshit Bansal +1
Simulation is a powerful tool to better understand physical systems, but generally requires computationally expensive numerical methods. Downstream applications of such simulations…
Fast Dynamic 1D Simulation of Divertor Plasmas with Neural PDE Surrogates
Yoeri Poels, Gijs Derks, Egbert Westerhof +3
Managing divertor plasmas is crucial for operating reactor scale tokamak devices due to heat and particle flux constraints on the divertor target. Simulation is an important tool t…
Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics
Koen Minartz, Yoeri Poels, Simon Koop +1
Neural networks are emerging as a tool for scalable data-driven simulation of high-dimensional dynamical systems, especially in settings where numerical methods are infeasible or c…
Towards Learned Simulators for Cell Migration
Koen Minartz, Yoeri Poels, Vlado Menkovski
Simulators driven by deep learning are gaining popularity as a tool for efficiently emulating accurate but expensive numerical simulators. Successful applications of such neural si…