Latent Field Discovery In Interacting Dynamical Systems With Neural Fields

arXiv:2310.20679v2 Announce Type: replace
Abstract: Systems of interacting objects often evolve under the influence of field effects that govern their dynamics, yet previous works have abstracted away from such effects, and assume that systems evolve in a vacuum. In this work, we focus on discovering these fields, and infer them from the observed dynamics alone, without directly observing them. We theorize the presence of latent force fields, and propose neural fields to learn them. Since the observed dynamics constitute the …

abstract arxiv cs.lg discovery dynamics effects fields focus influence objects stat.ml systems them type vacuum work