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09/21/2022
Designing PIDs for Reproducible Science Using Time-Series Data
As part of the investigation done by the IEEE Standards Association P295...
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09/16/2020
Exploring Bayesian Surprise to Prevent Overfitting and to Predict Model Performance in Non-Intrusive Load Monitoring
Non-Intrusive Load Monitoring (NILM) is a field of research focused on s...
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08/22/2020
Investigating the Performance Gap between Testing on Real and Denoised Aggregates in Non-Intrusive Load Monitoring
Prudent and meaningful performance evaluation of algorithms is essential...
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01/20/2020
Towards Comparability in Non-Intrusive Load Monitoring: On Data and Performance Evaluation
Non-Intrusive Load Monitoring (NILM) comprises of a set of techniques th...
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12/12/2019
On Metrics to Assess the Transferability of Machine Learning Models in Non-Intrusive Load Monitoring
To assess the performance of load disaggregation algorithms it is common...
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05/14/2017
RAE: The Rainforest Automation Energy Dataset for Smart Grid Meter Data Analysis
Datasets are important for researchers to build models and test how well...
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03/24/2016