Computer implemented machine learning system and a method for operating the machine learning system for determining a time series

A non-transitory computer readable storage medium on which is stored a computer program for operating a machine learning system for determining a time series, the computer program, when executed by computer, causes the computer to perform the following steps:

• providing an input for a first generative model depending on a probabilistic variable, the probabilistic variable being noise;
• and
• determining an output of the first model in response to the input for the first model, wherein the output of the first model characterizes the time series, the first model including a first layer that is trained to map the input for the first model determined depending on the probabilistic variable to output characterizing intermediate data, the first model further including a second layer that is trained to map the intermediate data to the time series depending on an output of a third layer of the first model, the output of the third layer characterizing a physical constraint to a machine state, and wherein values of the time series or the intermediate data are constrained by the output of the third layer.