31 citations · 31 across the 2 of their papers we have counts for
2 papers
math.DS2023
The Collective Dynamics of a Stochastic Port-Hamiltonian Self-Driven Agent Model in One Dimension
Matthias Ehrhardt, Thomas Kruse, Antoine Tordeux
The collective motion of self-driven agents is a phenomenon of great interest in interacting particle systems. In this paper, we develop and analyze a model of agent motion in one…
cs.LG2023★ 31 cited
PINN Training using Biobjective Optimization: The Trade-off between Data Loss and Residual Loss
Fabian Heldmann, Sarah Berkhahn, Matthias Ehrhardt +1
Physics informed neural networks (PINNs) have proven to be an efficient tool to represent problems for which measured data are available and for which the dynamics in the data are…