Learning minimal representations of stochastic processes with variational autoencoders

Stochastic processes have found numerous applications in science, as they are broadly used to model a variety of natural phenomena. The dataset consists of trajectories of stochastic processes, including Brownian motion, fractional Brownian motion, and scaled Brownian motion.