Electrostatic field dataset - Latent Field Discovery in Interacting Dynamical Systems with Neural Fields

Creators
Publication date 13-12-2023
Description
This repository contains the "Electrostatic field" dataset from the paper Latent Field Discovery in Interacting Dynamical Systems with Neural Fields Miltiadis Kofinas, Erik J Bekkers, Naveen Shankar Nagaraja, Efstratios Gavves NeurIPS 2023 https://arxiv.org/abs/2310.20679 https://github.com/mkofinas/aether It contains simulations of trajectories of 5 charged particles in 2 dimensions, interacting via Coulomb forces. Particles move under the influence of 20 immovable and unknown sources, which are shared in the whole dataset. There are 50,000 simulations for training, 10,000 for validation, and 10,000 for testing. Simulations last for 49 timesteps. The features comprise positions and velocities of particles, while edges describe the product of pairwise charges. The dataset also contains the positions of the field sources, meant to be used for visualization.
Publisher Zenodo
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Document type Dataset
Related publication Latent Field Discovery in Interacting Dynamical Systems with Neural Fields
DOI https://doi.org/10.5281/zenodo.10631646
Other links https://zenodo.org10631646
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