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Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation
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Cited by
Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey
Zoha, A., Gluhak, A., Imran, M., & Rajasegarar, S. (2012) · Sensors · doi:10.3390/s121216838 · Cited by 954
Is disaggregation the holy grail of energy efficiency? The case of electricity
Carrie Armel, K., Gupta, A., Shrimali, G., & Albert, A. (2013) · Energy Policy · doi:10.1016/j.enpol.2012.08.062 · Cited by 595
NILMTK: an open source toolkit for non-intrusive load monitoring
Batra, N., Kelly, J., Parson, O., Dutta, H., Knottenbelt, W., Rogers, A., Singh, A., & Srivastava, M. (2014) · Proceedings of the 5th international conference on Future energy systems · doi:10.1145/2602044.2602051 · Cited by 502
Non-Intrusive Load Monitoring Using Prior Models of General Appliance Types
Parson, O., Ghosh, S., Weal, M., & Rogers, A. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v26i1.8162 · Cited by 354
Transfer Learning for Non-Intrusive Load Monitoring
D'Incecco, M., Squartini, S., & Zhong, M. (2020) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2019.2938068 · Cited by 330
Metadata
- Authors
- Kolter, J. Z., & Jaakkola, T.
- Venue
- DSpace@MIT (Massachusetts Institute of Technology)
- Publisher
- Massachusetts Institute of Technology
- Published
- 2018-06-30
- Volume
- 22
- Pages
- 1472-1482
- OpenAlex
- W1138573735
- Cited by
- 453
- References
- 0
- FWCI
- 21.64
- Type
- conference paper
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation. https://app.cochat.ai/papers/10.1184/r1/6603563
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- Kolter, J. Z., & Jaakkola, T. (2018). Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation. DSpace@MIT (Massachusetts Institute of Technology). https://doi.org/10.1184/r1/6603563
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
