Jülich Aachen Research Alliance

Robust design of multi-energy systems accounting for mixed-integer operational problems

Identifying robust designs for multi-energy systems is computationally challenging. As rigorous approaches are often computationally intractable, heuristics are employed to generate candidate designs. Specifically, we consider a heuristic that iteratively identifies and adds extr...

DifferentiableThermodynamic Phase-Equilibria forMachine Learning

Abstract Accurate prediction of phase equilibria remains a central challenge in chemical engineering. Physics-consistent machine learning methods that incorporate thermodynamic structure into neural networks have recently shown strong performance for activity-coefficient modeling...

A quality measure for repeating multiple-unit spike patterns

We propose a quality measure for spatio-temporal spike patterns (STPs) in multiple-neuron recordings. In such recordings, repeating STPs or pattern repetitions (PRs) are often found, with many of these generated by chance. To rule those out, statistical tests have been developed...