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cs.LG2025
Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systems
Hans Harder, Abhijeet Vishwasrao, Luca Guastoni +2
This paper is concerned with probabilistic techniques for forecasting dynamical systems described by partial differential equations (such as, for example, the Navier-Stokes equatio…
cs.LG2025
Surrogate Modeling of 3D Rayleigh-Benard Convection with Equivariant Autoencoders
Fynn Fromme, Hans Harder, Christine Allen-Blanchette +1
The use of machine learning for modeling, understanding, and controlling large-scale physics systems is quickly gaining in popularity, with examples ranging from electromagnetism o…
cs.LG2024
Solving Partial Differential Equations with Equivariant Extreme Learning Machines
Hans Harder, Jean Rabault, Ricardo Vinuesa +2
We utilize extreme-learning machines for the prediction of partial differential equations (PDEs). Our method splits the state space into multiple windows that are predicted individ…