Neural Fields for Interactive Visualization of Statistical Dependencies in 3D Simulation Ensembles

arXiv:2307.02203v5 Announce Type: replace
Abstract: We present the first neural network that has learned to compactly represent and can efficiently reconstruct the statistical dependencies between the values of physical variables at different spatial locations in large 3D simulation ensembles. Going beyond linear dependencies, we consider mutual information as a measure of non-linear dependence. We demonstrate learning and reconstruction with a large weather forecast ensemble comprising 1000 members, each storing multiple physical variables at a 250 x 352 x 20 simulation …

abstract arxiv beyond cs.cv dependencies fields information interactive linear locations network neural network simulation spatial statistical type values variables visualization