116 citations · 193 across the 15 of their papers we have counts for
4 papers · 1 filter
Global and Local Reduced Models for Interacting, Heterogeneous Agents
Thomas N. Thiem, Felix P. Kemeth, Tom Bertalan +2
Large collections of coupled, heterogeneous agents can manifest complex dynamical behavior presenting difficulties for simulation and analysis. However, if the collective dynamics…
Learning emergent PDEs in a learned emergent space
Felix P. Kemeth, Tom Bertalan, Thomas Thiem +4
We extract data-driven, intrinsic spatial coordinates from observations of the dynamics of large systems of coupled heterogeneous agents. These coordinates then serve as an emergen…
Emergent spaces for coupled oscillators
Thomas N. Thiem, Mahdi Kooshkbaghi, Tom Bertalan +2
In this paper we present a systematic, data-driven approach to discovering "bespoke" coarse variables based on manifold learning algorithms. We illustrate this methodology with the…
Dimension reduction in heterogeneous neural networks: generalized Polynomial Chaos (gPC) and ANalysis-Of-VAriance (ANOVA)
Minseok Choi, Tom Bertalan, Carlo R. Laing +1
We propose, and illustrate via a neural network example, two different approaches to coarse-graining large heterogeneous networks. Both approaches are inspired from, and use tools…