{"id":73534,"url":"https://github.com/klemenjak/nilm-papers-with-code","name":"nilm-papers-with-code","description":"An archive for NILM papers with source code and other supplemental material","projects_count":31,"last_synced_at":"2026-07-23T08:00:23.444Z","repository":{"id":43704137,"uuid":"225835787","full_name":"klemenjak/nilm-papers-with-code","owner":"klemenjak","description":"An archive for NILM papers with source code and other supplemental material","archived":false,"fork":false,"pushed_at":"2024-01-19T15:03:03.000Z","size":30,"stargazers_count":146,"open_issues_count":0,"forks_count":26,"subscribers_count":10,"default_branch":"master","last_synced_at":"2026-07-04T17:03:22.622Z","etag":null,"topics":["awesome-list","energy-disaggregation","non-intrusive-load-monitoring","papers-collection","papers-with-code","reproducible-paper","reproducible-research","scholarship","source-code"],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/klemenjak.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":".github/FUNDING.yml","license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null},"funding":{"github":null,"patreon":null,"open_collective":null,"ko_fi":null,"tidelift":null,"community_bridge":null,"liberapay":null,"issuehunt":null,"otechie":null,"custom":null}},"created_at":"2019-12-04T10:03:33.000Z","updated_at":"2026-06-23T06:24:24.000Z","dependencies_parsed_at":"2024-10-27T11:08:44.012Z","dependency_job_id":"02687013-4498-4cbb-bead-716d738e6ff4","html_url":"https://github.com/klemenjak/nilm-papers-with-code","commit_stats":{"total_commits":15,"total_committers":4,"mean_commits":3.75,"dds":0.5333333333333333,"last_synced_commit":"cf5628293d5b0a99349f881d7cd3319e34297f67"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/klemenjak/nilm-papers-with-code","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/klemenjak%2Fnilm-papers-with-code","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/klemenjak%2Fnilm-papers-with-code/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/klemenjak%2Fnilm-papers-with-code/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/klemenjak%2Fnilm-papers-with-code/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/klemenjak","download_url":"https://codeload.github.com/klemenjak/nilm-papers-with-code/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/klemenjak%2Fnilm-papers-with-code/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":35794548,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-07-20T02:08:10.276Z","status":"online","status_checked_at":"2026-07-23T02:00:06.683Z","response_time":57,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"created_at":"2024-10-11T15:26:52.869Z","updated_at":"2026-07-23T08:00:23.444Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["Algorithms","Datasets","Toolkits","Metrics \u0026 Performance Evaluation","Misc","Licence"],"sub_categories":["Neural Nets","Graph Signal Processing","Mathematical Optimization"],"readme":"[![Tip Me via PayPal](https://img.shields.io/badge/PayPal-tip%20me-green.svg?logo=paypal)](https://www.paypal.me/ChristophKlemenjak)\n\n![](http://wwwu.aau.at/chklemen/Untitled-49.png)\n\nReproducibility of scientific contributions is an important aspect of scholarship that has received way to little attention! This repository aims to collect information on peer-reviewed NILM (alias energy disaggregation) papers that have been published with source code or extensive supplemental material. We group NILM papers based on a number of categories: algorithms, toolkits, datasets, and misc. Feel free to contribute to this repository! Please consider our \"style guide\":\n\n- **This is a title.** (year). [[pdf]](link-to-pdf) [[code]](link-to-code)\n  - Main Author et al. Optional: *Acronym of conference or journal* i.e. Where was it published?\n\n\u003c!--\n- **.** (). [[pdf]]() [[code]]()\n  -  et al. *Venue.*\n--\u003e\n\n\n## Algorithms\n\n### Graph Signal Processing\n\n- **On a Training-Less Solution for Non-Intrusive Appliance Load Monitoring Using Graph Signal Processing** (2016). [[pdf]](https://ieeexplore.ieee.org/document/7457610) [[code]](https://github.com/loneharoon/GSP_energy_disaggregator)\n  - B. Zhao et al. *IEEE Access.*\n\n### Hidden Markov Models\n\n- **Exploiting HMM Sparsity to Perform Online Real-Time Nonintrusive Load Monitoring (NILM).** (2015). [[pdf]](http://makonin.com/doc/TSG_2015.pdf) [[code]](https://github.com/smakonin/SparseNILM)\n  - S. Makonin et al. *IEEE TSG.*\n\n### Mathematical Optimization\n\n- **Mixed-Integer Nonlinear Programming for State-based Non-Intrusive Load Monitoring.** (2022). [[link]](https://ieeexplore.ieee.org/document/9714495) [[code]](https://github.com/antoniosudoso/nilm-bqp)\n  - M. Balletti et al. *IEEE TSG.**\n\n### Neural Nets\n\n- **Improving Non-Intrusive Load Disaggregation through an Attention-Based Deep Neural Network.** (2021). [[pdf]](https://www.mdpi.com/1996-1073/14/4/847/pdf) [[code]](https://github.com/antoniosudoso/attention-nilm)\n  - V. Piccialli et al. *Energies*\n\n- **Pruning Algorithms for Seq2Point Energy Disaggregation.** (2020). [[pdf]]() [[code]](https://github.com/JackBarber98/pruned-nilm)\n  - J. Barber et al. *.*\n\n- **Transfer Learning for Non-Intrusive Load Monitoring.** (2019). [[pdf]]() [[code]](https://github.com/MingjunZhong/transferNILM)\n  - D. Michele et al. *IEEE TSG.*\n\n- **Neural NILM: Deep neural networks applied to energy disaggregation** (2015) [[pdf]](http://jack-kelly.com/files/writing/neural_nilm.pdf) [[code]](https://github.com/JackKelly/neuralnilm)\n  - J. Kelly et al. *BuildSys'15*\n\n- **Sliding Window Approach for Online Energy Disaggregation Using Artificial Neural Networks.** (2018). [[pdf]](https://dl.acm.org/citation.cfm?doid=3200947.3201011) [[code]](https://github.com/OdysseasKr/online-nilm)\n    - O. Krystalakos et al. *Venue.*\n\n- **Sequence-to-point learning with neural networks for non-intrusive load monitoring** (2018) [[pdf]](https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16623/15980) [[code]](https://github.com/MingjunZhong/NeuralNetNilm)\n  - C. Zhang et al. *AAAI'18*\n\n- **WaveNILM: A causal neural network for power disaggregation from the complex power signal** (2019) [[pdf]](https://arxiv.org/pdf/1902.08736.pdf) [[code]](https://github.com/picagrad/WaveNILM)\n  - Alon Harell et al. *ICASSP'19*\n\n\n## Toolkits\n\n- **Towards reproducible state-of-the-art energy disaggregation.** (2019) [[pdf]](https://nipunbatra.github.io/papers/batra_buildsys_19.pdf) [[code]](https://github.com/nilmtk/nilmtk-contrib)\n  - N. Batra et al. *BuildSys'19.*\n\n\n- NILM-Eval [[pdf]]() [[code]](https://github.com/beckel/nilm-eval)\n- NILMTK [[pdf]](https://arxiv.org/pdf/1404.3878v1.pdf) [[code]](https://github.com/nilmtk/nilmtk)\n\n## Metrics \u0026 Performance Evaluation\n\n- **Nonintrusive load monitoring (NILM) performance evaluation.** (2015). [[pdf]](https://link.springer.com/article/10.1007%2Fs12053-014-9306-2) [[code]](https://github.com/smakonin/NILM_PerformanceEval)\n  -  S. Makonin et al. *Springer Energy Efficiency.*\n\n- **Towards Comparability in Non-Intrusive Load Monitoring: On Data and Performance Evaluation** [[pdf]](http://makonin.com/doc/ISGT-NA_2020b.pdf) [[code]]()\n  - C. Klemenjak et al. 2020 IEEE ISGT.\n\n## Misc\n\n- **Device-Free User Activity Detection using Non-Intrusive Load Monitoring: A Case Study.** (2020). [[pdf]](https://www.areinhardt.de/publications/2020/Reinhardt_DFHS_2020.pdf) [[code]](https://github.com/klemenjak/antgen)\n    - A. Reinhardt et al. *DFHS Workshop.*\n\n- **Machine learning approaches for non-intrusive load monitoring: from qualitative to quantitative comparation, Artificial Intelligence Review** (2018). [[pdf]](https://intelligence.csd.auth.gr/publications/machine-learning-approaches-for-non-intrusive-load-monitoring-from-qualitative-to-quantitative-comparation/) [[code]](https://github.com/ChristoferNal/power-disaggregation-complexity)\n  - C. Nalmpantis et al. *Artificial Intelligence Review.*\n\n- **Metadata for Energy Disaggregation.** (2014) [[pdf]](https://ieeexplore.ieee.org/document/6903193) [[code]](https://github.com/nilmtk/nilm_metadata)\n  - J. Kelly et al. *CDS'14.*\n\n- **On time series representations for multi-label NILM.** (2020) [[pdf]](https://link.springer.com/epdf/10.1007/s00521-020-04916-5?sharing_token=bTZg6CBADDbWx7UVvztexPe4RwlQNchNByi7wbcMAY4YyOCPZ8jI-u3LyC4lDtEOZIQACACm_MVY_633J4jzg0CtjGEkhvPkzOs5Z-2UGgB1P_m1_4nDnPxtIplmNRaDx7TM52V6MVQYVJPSqJEKpxv1n3RqXoEm1ZpW5amjaaA%3D) [[code]](https://github.com/ChristoferNal/multi-nilm)\n  - C. Nalmpantis et al. *Springer Neural Computing and Applications.*\n\n## Datasets\n\n#### Real-World Datasets\n\n- REDD [[link]](https://web.archive.org/web/20220812015008/http://redd.csail.mit.edu/)\n- UK-DALE [[link]](https://www.nature.com/articles/sdata20157)\n- BLUED [[link]](http://portoalegre.andrew.cmu.edu:88/BLUED/)\n- GREEND [[link]](https://sourceforge.net/projects/greend/)\n- AMPds [[link]](http://ampds.org/)\n- ECO [[link]](http://www.vs.inf.ethz.ch/res/show.html?what=eco-data)\n- HES [[link]](http://randd.defra.gov.uk/Default.aspx?Menu=Menu\u0026Module=More\u0026Location=None\u0026ProjectID=17359\u0026FromSearch=Y\u0026Publisher=1\u0026SearchText=EV0702\u0026SortString=ProjectCode\u0026SortOrder=Asc\u0026Paging=10#Description)\n- Tracebase [[link]](https://github.com/areinhardt/tracebase)\n- PLAID [[link]](http://www.plaidplug.com/)\n- ENERTALK [[link]](https://www.nature.com/articles/s41597-019-0212-5)\n\n\n#### Synthetic Datasets and Generators\n\n- **SmartSim: A Device-Accurate Smart Home Simulator for Energy Analytics.** (2016). [[pdf]](http://www.ecs.umass.edu/~irwin/smartsim.pdf) [[code]](https://github.com/sustainablecomputinglab/smartsim)\n    - D. Chen et al. *SmartGridComm'16.*\n\n- **How does Load Disaggregation Performance Depend on Data Characteristics? Insights from a Benchmarking Study.** (2020). [[pdf]](https://www.areinhardt.de/publications/2020/Reinhardt_eEnergy_2020.pdf) [[code]](https://github.com/klemenjak/antgen)\n    - A. Reinhardt et al. *ACM e-energy.*\n\n- **A synthetic energy dataset for non-intrusive load monitoring in households.** (2020). [[pdf]](https://www.nature.com/articles/s41597-020-0434-6) [[code]](https://github.com/klemenjak/SynD)\n    - C. Klemenjak et al. *Scientific Data.*\n\n\n## Licence\n[![CC0](http://mirrors.creativecommons.org/presskit/buttons/88x31/svg/cc-zero.svg)](https://creativecommons.org/publicdomain/zero/1.0/)\n\nTo the extent possible under law, [Christoph Klemenjak](https://github.com/klemenjak) has waived all copyright and related or neighbouring rights to this work.\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/klemenjak%2Fnilm-papers-with-code/projects"}