Non-intrusive load monitoring: A review and outlook. - Christoph Klemenjak; Peter Goldsborough (GI-Jahrestagung, 2016)

YoMo: the Arduino-based smart metering board. - Christoph Klemenjak; Dominik Egarter; Wilfried Elmenreich (Comput. Sci. Res. Dev., 2016)

On the applicability of correlation filters for appliance detection in smart meter readings. - Christoph Klemenjak; Wilfried Elmenreich (SmartGridComm, 2017)

Yay - an open-hardware energy measurement system for feedback and appliance detection based on the arduino platform. - Christoph Klemenjak; Wilfried Elmenreich (WISES, 2017)

On performance evaluation and machine learning approaches in non-intrusive load monitoring. - Christoph Klemenjak (Energy Inform., 2018)

Electricity Consumption Data Sets: Pitfalls and Opportunities. - Christoph Klemenjak; Andreas Reinhardt 001; Lucas Pereira; Stephen Makonin; Mario Bergés; Wilfried Elmenreich (BuildSys, 2019)

On Metrics to Assess the Transferability of Machine Learning Models in Non-Intrusive Load Monitoring. - Christoph Klemenjak; Anthony Faustine; Stephen Makonin; Wilfried Elmenreich (CoRR, 2019)

How does Load Disaggregation Performance Depend on Data Characteristics?: Insights from a Benchmarking Study. - Andreas Reinhardt 001; Christoph Klemenjak (e-Energy, 2020)

Augmenting an Assisted Living Lab with Non-Intrusive Load Monitoring. - Hafsa Bousbiat; Christoph Klemenjak; Gerhard Leitner; Wilfried Elmenreich (I2MTC, 2020)

Towards Comparability in Non-Intrusive Load Monitoring: On Data and Performance Evaluation. - Christoph Klemenjak; Stephen Makonin; Wilfried Elmenreich (ISGT, 2020)

Exploring Time Series Imaging for Load Disaggregation. - Hafsa Bousbiat; Christoph Klemenjak; Wilfried Elmenreich (BuildSys, 2020)

On the Relationship between Seasons of the Year and Disaggregation Performance. - João Gois; Christoph Klemenjak; Lucas Pereira (NILM@SenSys, 2020)

Stop: Exploring Bayesian Surprise to Better Train NILM. - Richard Jones; Christoph Klemenjak; Stephen Makonin; Ivan V. Bajic (NILM@SenSys, 2020)

Exploring Bayesian Surprise to Prevent Overfitting and to Predict Model Performance in Non-Intrusive Load Monitoring. - Richard Jones; Christoph Klemenjak; Stephen Makonin; Ivan V. Bajic (CoRR, 2020)

Investigating the performance gap between testing on real and denoised aggregates in non-intrusive load monitoring. - Christoph Klemenjak; Stephen Makonin; Wilfried Elmenreich (Energy Inform., 2021)

Adaptive Weighted Recurrence Graphs for Appliance Recognition in Non-Intrusive Load Monitoring. - Anthony Faustine; Lucas Pereira; Christoph Klemenjak (IEEE Trans. Smart Grid, 2021)

Neural NILM Learning Paradigms: From Centralised to Decentralised Learning. - Hafsa Bousbiat; Christoph Klemenjak; Yassine Himeur; Wilfried Elmenreich; Abbes Amira; Wathiq Mansoor; Shadi Atalla (ICSPIS, 2022)

Unlocking the Full Potential of Neural NILM: On Automation, Hyperparameters, and Modular Pipelines. - Hafsa Bousbiat; Anthony Faustine; Christoph Klemenjak; Lucas Pereira; Wilfried Elmenreich (IEEE Trans. Ind. Informatics, 2023)