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stat.ML2023
Wiener Chaos in Kernel Regression: Towards Untangling Aleatoric and Epistemic Uncertainty
T. Faulwasser, O. Molodchyk
Gaussian Processes (GPs) are a versatile method that enables different approaches towards learning for dynamics and control. Gaussianity assumptions appear in two dimensions in GPs…
eess.SY2023
System-level Testing of the Congestion Management Capability of a Hardware-Independent Optimal Power Flow Algorithm
Thomas Schwierz, Rajkumar Palaniappan, Oleksii Molodchyk +1
The integration of distributed energy resources (DERs) into the electrical grid causes various challenges in the distribution grids. The complexity of smart grids as multi-domain e…