no code implementations • 27 May 2024 • Yoeri Poels, Koen Minartz, Harshit Bansal, Vlado Menkovski
Simulation is a powerful tool to better understand physical systems, but generally requires computationally expensive numerical methods.
1 code implementation • 26 May 2024 • Pol Timmer, Koen Minartz, Vlado Menkovski
In this paper, we introduce the Crystal Growth Neural Emulator (CGNE), a probabilistic model for efficient crystal growth emulation at the mesoscopic scale that overcomes these challenges.
no code implementations • 30 May 2023 • Yoeri Poels, Gijs Derks, Egbert Westerhof, Koen Minartz, Sven Wiesen, Vlado Menkovski
State-of-the-art neural PDE surrogates are evaluated in a common framework and extended for properties of the DIV1D data.
1 code implementation • NeurIPS 2023 • Koen Minartz, Yoeri Poels, Simon Koop, Vlado Menkovski
However, to incorporate symmetries in probabilistic neural simulators that can simulate stochastic phenomena, we need a model that produces equivariant distributions over trajectories, rather than equivariant function approximations.
no code implementations • 2 Oct 2022 • 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.