My name is Oliver Parson, and I'm currently employed as a Senior Data Scientist at Bulb. I'm interested in investigating the ways in which machine learning can be used to break down household energy consumption data into individual appliances, also known as Non-intrusive Appliance Load Monitoring (NILM) or energy disaggregation.
Monday, 11 November 2019
Towards reproducible state-of-the-art energy disaggregation
This week Nipun Batra will present a paper which aims to improve the reproducibility of state-of-the-art NILM at BuildSys 2019 in New York. The full paper is available online, which describes the new experiment and disaggregator APIs in NILMTK, along with a number of algorithms implemented in the nilmtk-contrib repository. The work will also be presented during the demo session to give NILM researchers some hands on experience using NILMTK's new disaggregation algorithms.
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