Generate realistic sequential data with this easy-to-train model. This article explores using Variational Autoencoders (VAEs) to model and generate time series data. It details the specific architecture choices, like 1D convolutional layers and a seasonally dependent prior, used to capture the periodic and sequential patterns in temperature data.