{"as_of":"2026-08-19T04:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a68db5489cd5b0e31915e46067843115da48cc392f2bd3e31853d266ba45a548","coverage":[{"denominator":20,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":20,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-24T15:10:17.814329Z","state":"measured"},{"denominator":20,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":20,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/1907.11738/citation-record","integrity":"/paper/1907.11738/integrity","json":"/paper/1907.11738/citation-record.json","paper":"/paper/1907.11738"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Synchronized phasor measurement applications in power systems","venue":null,"work_id":"5a0a7237-0ab6-4dc1-a3e8-8bfc25a39592","year":2010},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:6fd1f69c3e24463ebee26fd6dc42e72f1fe0c4fcfbf1706183863b32e2580a00","observation_id":"8e81d822-9e10-4d27-a53b-1a3a8bda9a45","resolution":{"observed_at":"2026-05-24T15:16:15.244412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A Multi -model Combination Approach for Probabilistic Wind Power Forecasting","venue":null,"work_id":"2be3b82e-b6a6-41d8-919c-878e5501dc1e","year":2018},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:e43c3263e9cb3cf8d93556d8eac45c1ede870ee01df3feb23a9c4418caa4344c","observation_id":"44be702e-33e2-4610-a974-19d363f88a4b","resolution":{"observed_at":"2026-05-24T15:16:15.234506Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A new fault-location algorithm for series-compensated double-circuit transmission lines based on the distributed parameter model","venue":null,"work_id":"4f6759bd-5bf9-415c-b1e9-776446d0c67d","year":2017},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:188af312021e3e2c25fc1469013e5e7c7e4c07c97071b65b4f666aba894fb608","observation_id":"6d2c4ecd-a76c-4f36-9918-f30993cce0f7","resolution":{"observed_at":"2026-05-24T15:16:15.238044Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Online Calibratio n of Phasor Measurement Unit U sing Density-Based Spatial Clustering","venue":null,"work_id":"a7fcc88d-e599-40ca-9df0-ed63a6d33b08","year":2018},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:408d41f7faf8a6404f4c156f8b1a6b7b96310615a5bbed0ff1ce437f40191d15","observation_id":"e390b199-0a2d-4ecf-a6f6-6b8865f3199a","resolution":{"observed_at":"2026-05-24T15:16:15.232283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A Nonlinear Regression Application via Machine Learning Techniques for Geomagnetic Data Reconstruction Processing","venue":null,"work_id":"f9d3887f-4dfb-46b7-8295-5ea8643317b6","year":2018},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:6d974167d28aaddb81b0cd319df359f826b7f6d7440fdd7d706f72be12c7b36f","observation_id":"32ef02e7-e401-4cac-896c-e771cd5bdbec","resolution":{"observed_at":"2026-05-24T15:16:15.229298Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"High - dimensional and large -scale anomaly detection using a linear one - class SVM with deep learning","venue":null,"work_id":"c1527471-1620-4862-b970-e8e0e69a191f","year":2016},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:c0a9ceb126523bf487fac1e24d796d68f20243661f9b354a67cb59f658a06c40","observation_id":"75148c71-6bf4-4d61-9e83-600a0f2f4bca","resolution":{"observed_at":"2026-05-24T15:16:15.222213Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A simple method for reconstructing a high -quality NDVI time-series data set based on the Savitzky –Golay filter","venue":null,"work_id":"c00b3aa7-039e-4644-ad93-6a2db7818154","year":2004},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:9bdebad5818fd79bb397f5002ebc804bb4a6c04f514d28a668e72dfcb361b768","observation_id":"ab57de41-12c8-4833-b73b-84069bb829d9","resolution":{"observed_at":"2026-05-24T15:16:15.217894Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Interpolation, realization, and reconstruction of noisy, irregularly sampled data","venue":null,"work_id":"340fb02b-ce83-4278-9a55-51f7f11e7d27","year":1992},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:e16697be56687db301d4a322a203047db4fcc3d52c2024d22184530d9688a7f0","observation_id":"fa32fe45-d59c-4e73-840b-b5311b1de978","resolution":{"observed_at":"2026-05-24T15:16:15.247810Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Multimodal autoencoder: A dee p learning approach to filling in missing sensor data and enabling better mood prediction","venue":null,"work_id":"01437534-c6da-4cf3-8270-9c36f6592b95","year":2017},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:e2c3c30d4f13197d3017d4b75513c3e8eca1a3a6adcae12d545a0564a7fd8bb9","observation_id":"b8a4de16-13ac-46ab-93e7-c14c57225ba5","resolution":{"observed_at":"2026-05-24T15:16:15.216102Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Reconstructing Cloud-Contaminated Multispectral Images With Contextualized Autoencoder Neural Networks","venue":null,"work_id":"2a799fbf-c087-4dfa-b5e8-6748b94bb44f","year":2018},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:259d5f43f2da8d78a6da7424c503ce92432e320173f3c8562b53879c19cf981e","observation_id":"c09b8dfc-6b2f-4911-9bd2-24241d6d6f93","resolution":{"observed_at":"2026-05-24T15:16:15.235287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Noi se removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time","venue":null,"work_id":"00e22038-96b0-44c4-bca7-e8d3e1fe3de7","year":2003},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:7a95072c8342365d2c6e87461b11bba26a4f25e91c3eba973893f7eedd1d0908","observation_id":"5622ad09-6d75-4985-b6d7-58b345f0c293","resolution":{"observed_at":"2026-05-24T15:16:15.226364Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Re construction of seismic data with missing traces using normalized gaussian weighted filter","venue":null,"work_id":"68372b9f-be37-497e-85dd-b195e3bb5711","year":2018},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:34e40a14edf071e9c08393dc8124d3b66e2bc3a103fdc673dff3a8ec13a20e0b","observation_id":"91de69b6-f46e-4d4f-8acb-1644ced6072d","resolution":{"observed_at":"2026-05-24T15:16:15.206637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Reconstructing missing data in state estimation with autoencoders","venue":null,"work_id":"129d2407-e37d-4938-929a-6f727d708780","year":2012},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:0072439c83b45599a7fec75d3f1098fdcb2d01727cb803646072cefe1bddb10e","observation_id":"f4a35984-2139-4736-b7a6-dd0b14a12dc4","resolution":{"observed_at":"2026-05-24T15:16:15.241303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Split -brain autoencoders: Unsupervised learning by cross -channel prediction","venue":null,"work_id":"42e8b40f-b9ee-417c-905b-ddcffb52c002","year":2017},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:715b67308377e856eb6f533bfdac9a1853954e39aa36737c2d0e39e8165c0cf8","observation_id":"8c9fcede-906f-4450-ae0b-69a37000c9c4","resolution":{"observed_at":"2026-05-24T15:16:15.220573Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Analytical investigation of autoencoder-based methods for unsupervised anomaly detection in building energy data","venue":null,"work_id":"7e5bc698-48eb-4709-b910-6ed2613d78a1","year":2018},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:30dd7d878b5d82714aa45ed2034e8778770445bae8dae6e3debba619d6c3de32","observation_id":"2dca0e82-fc82-4d84-880a-0be797b052e9","resolution":{"observed_at":"2026-05-24T15:16:15.204524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Generalized autoencoder: A neural network framework for dimensionality reduction","venue":null,"work_id":"cebfa848-6a8b-48d2-bc19-01f62d7ad817","year":2014},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:4876ec96e2dff4f182a9f111b1c048ac315817cd069ece8eb3224eab6c24e5f6","observation_id":"33109b4e-402e-4c75-9293-5ee1a78c5d48","resolution":{"observed_at":"2026-05-24T15:16:15.195171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Extracting a nd composing robust features with denoising autoencoders","venue":null,"work_id":"02719de4-a541-4cef-aea9-8e0d7e26f8b6","year":2008},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:48cb667c1ebc4152e21ffbb82c045c3585b9d7dd13a68ef20d54411012717f5e","observation_id":"cf332852-6bd7-498c-bbcb-f013283b1b77","resolution":{"observed_at":"2026-05-24T15:16:15.197519Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Autoencoders, unsupervised learning, and deep architectures","venue":null,"work_id":"5fea13be-a422-4f4b-a8b2-34dd7560cbda","year":2012},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:848d0f23194b46955937681ef1f0aef9275f29ddf5609beb077ada6099f4cfcd","observation_id":"7aeb909e-1262-4ec8-940c-14185dacd323","resolution":{"observed_at":"2026-05-24T15:16:15.202232Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Long short-term memory","venue":null,"work_id":"fc663201-4be1-49f7-8a2c-3dc011dfa79f","year":1997},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:15490b7f3f100e50e3cb8c5f0388a31da8a7306b70ea7a9b6c55cbb9ea81684c","observation_id":"cb616203-4e58-4da4-a7fe-65fd0d011e78","resolution":{"observed_at":"2026-05-24T15:16:15.250485Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A taxonom y of North American radial distribution feeders","venue":null,"work_id":"5c1bda93-3e01-419e-9b26-380a505560fc","year":2009},"citing_paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-24T15:10:17.814329Z"},"links":{"citing_paper":"/paper/1907.11738"},"observation_digest":"sha256:2c7c2e9d17c9578d5235b47e59dd50ee877ad59ad3bebad76f3a23b438d1ae4e","observation_id":"0fe9014f-ae81-4297-9b74-6e6a3ddfc40a","resolution":{"observed_at":"2026-05-24T15:16:15.209898Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1907.11738","last_updated":"2019-07-26T18:10:35Z","latest_version":1,"primary_category":"eess.SP","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:10:35Z","title":"Reconstruction of Power System Measurements Based on Enhanced Denoising Autoencoder"},"reference_resolution":{"displayed":20,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":20},"total_outbound_references":20},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:1907.11738."}