29 citations · 90 across the 15 of their papers we have counts for
15 papers
Decomposing Ensemble Spread in Lorenz '96 With Learned Stochastic Parameterizations
Birgit Kühbacher, Daan Crommelin, Niki Kilbertus
Weather and climate forecasts are inherently uncertain due to chaotic dynamics, imperfect initial conditions, and incomplete representation of the underlying physical processes. Op…
General perturbative framework for kinetics of rare transitions in 1-dimensional active particle systems
Vito Seinen, Peter G. Bolhuis, Daan Crommelin +2
We present a theoretical framework that enables investigating rare transitions in a general model of an active particle in an external potential, with the thermal Active Ornstein-U…
Asymptotic behavior for a general class of spreading models
K. M. D. Chan, D. T. Crommelin, M. R. H. Mandjes
Growing literatures on epidemic and rumor dynamics show that infection and information coevolve. We present a unified framework for modeling the spread of infection and information…
Reduced Data-Driven Turbulence Closure for Capturing Long-Term Statistics
Rik Hoekstra, Daan Crommelin, Wouter Edeling
We introduce a simple, stochastic, a-posteriori, turbulence closure model based on a reduced subgrid scale term. This subgrid scale term is tailor-made to capture the statistics of…
Data-driven dynamical coarse-graining for condensed matter systems
Mauricio J. del Razo, Daan Crommelin, Peter G. Bolhuis
Simulations of condensed matter systems often focus on the dynamics of a few distinguished components but require integrating the dynamics of the full system. A prime example is a…
Comparison of neural closure models for discretised PDEs
Hugo Melchers, Daan Crommelin, Barry Koren +2
Neural closure models have recently been proposed as a method for efficiently approximating small scales in multiscale systems with neural networks. The choice of loss function and…