Energy Time-Series Features for Emerging Applications on the Basis of Human-Readable Machine Descriptions. - Michael Vollmer 001; Adrian Englhardt; Holger Trittenbach; Pawel Bielski; Shahab Karrari; Klemens Böhm (e-Energy, 2019)

An Evaluation of NILM Approaches on Industrial Energy-Consumption Data. - Florian Kalinke; Pawel Bielski; Snigdha Singh; Edouard Fouché; Klemens Böhm (e-Energy, 2021)

Towards Automatically Refining Low-Quality Domain Knowledge: A Case Study in Healthcare. - Pawel Bielski; Sönke Jendral; Lena Witterauf; Jakob Bach (PKDD/ECML Workshops (3), 2023)

Knowledge-Guided Learning of Temporal Dynamics and its Application to Gas Turbines. - Pawel Bielski; Aleksandr Eismont; Jakob Bach; Florian Leiser; Dustin Kottonau; Klemens Böhm (e-Energy, 2024)

Quantifying Domain-Application Knowledge Mismatch in Ontology-Guided Machine Learning. - Pawel Bielski; Lena Witterauf; Sönke Jendral; Ralf Mikut; Jakob Bach (KEOD, 2024)

Micro Gas Turbine Electrical Energy Prediction. - Pawel Bielski; Dustin Kottonau (UCI-MLR, 2024)

Addressing Low-Quality Domain Knowledge in Knowledge-Guided Machine Learning. - Pawel Bielski (2025)