Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T00:53:56.699362Z
Paper Citation Record · LEDGER
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series
As of 14 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2608.00513.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
55 of 55 outbound references displayed
- verified exact3
- verified fuzzy31
- unresolved20
- parse uncertain1
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation a324d614-4460-4f79-ab68-13da52c0aa92 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 1
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation dd242442-ba32-430e-a2ce-45217ee8221b · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 2
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 330860ad-30c0-489a-8edc-2777cbf75acd · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 3
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:09.584220Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation c57f9817-c10d-48bc-abfc-55598244a224 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 4
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:09.260018Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation acd9b673-cacf-4002-ab5f-408f506dbfb3 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 5
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:09.000749Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 03a7c430-0a0c-4b99-a850-a5bfc3d7d685 · outbound
This paper cites When an appliance remains in a steady state, the electricity consumption profile on the supply circuit remains relatively stable.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series When an appliance remains in a steady state, the electricity consumption profile on the supply circuit remains relatively stable
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:08.681680Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 0647c6b0-b7eb-4585-8921-9c8090a66e74 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 7
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:08.316659Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 1f1e92c5-80c5-4fb4-bb34-3109752dee59 · outbound
This paper cites The thresholds Δ and ε are defined by inequality (1).
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series The thresholds Δ and ε are defined by inequality (1)
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:08.016074Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 7296a823-392d-4297-b2e4-ef5eb016dac1 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 9
- Resolution
- parse uncertain
- raw_fallback, observed 2026-08-05T00:54:07.682054Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation f6d5fbdd-9f13-42b5-8aba-0d8df29c0165 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 10
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:07.399370Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 174556b0-9e56-48b9-8990-a29eb4860738 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:07.162232Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation e0d76831-27fd-44ab-a922-cc6f2e4a4431 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:06.949580Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation e63a9b7c-36db-40ef-865e-9ec86d940c98 · outbound
This paper cites A novel segmentation approach for work mode boundary detection in MFR pulse sequence[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series A novel segmentation approach for work mode boundary detection in MFR pulse sequence[J]
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:01.207385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation dafaa72a-3709-4746-a2e5-b312ec46ec11 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 14
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:06.476898Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation eef20231-18a5-4563-973f-1e3dada82049 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 15
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:06.224565Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 5efd6f47-b639-45fc-817b-f0556aecb1d1 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 16
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:05.951721Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 3d662c3c-b605-4d69-aa02-0b4433b1f882 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 17
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:05.761274Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 696bdb06-6838-40ff-8d46-969c43f2ba11 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 18
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:05.492676Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 3c2de50b-376f-4757-ad2c-7d250019ef8b · outbound
This paper cites steady_segments are the output of Algorithm 2.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series steady_segments are the output of Algorithm 2
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:06.715940Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 97b6f5fb-b166-429e-9d1e-af9ad0f992a2 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 20
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:05.200692Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 972a13f2-4c72-48e7-a2ff-cd11e99bc70a · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 21
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:04.973535Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 41f1a2db-a93f-4f9d-a7ad-d1560dc614d9 · outbound
This paper cites Let 0 , ntt R ∈ with 0 0, 0ntt >> and 0 ntt <.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Let 0 , ntt R ∈ with 0 0, 0ntt >> and 0 ntt <
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:04.729155Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 2047b692-66cd-4f27-9d79-97ec2b859baa · outbound
This paper cites As shown in Figure 2, BayesSeg comprises a segmentation module, an evaluation module, and a parameter -optimization module.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series As shown in Figure 2, BayesSeg comprises a segmentation module, an evaluation module, and a parameter -optimization module
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:04.449223Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 99205b04-b81f-495c-ae40-9b7876ce410c · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 24
- Resolution
- verified exact
- raw_fallback, observed 2026-08-05T00:53:57.581048Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 6f05ed84-36cf-4a39-a25e-0a4a1aa76e42 · outbound
This paper cites making weight decisions for the user.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series making weight decisions for the user
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:04.195936Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 23a858c5-d3f9-4fb1-bdc5-548f958c3de9 · outbound
This paper cites A., ABID M.
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:03.899786Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 64b1eafe-5788-476f-8302-a922d611b756 · outbound
This paper cites A Survey of the Research on Non-intrusive Load Monitoring and Disaggregation[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series A Survey of the Research on Non-intrusive Load Monitoring and Disaggregation[J]
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:03.640919Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 101a1d7b-ea3a-490a-8575-a9e908c16208 · outbound
This paper cites Non -intrusive load monitoring: A systematic review of methods, scenario- specific challenges, and pathways to practical deployment[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Non -intrusive load monitoring: A systematic review of methods, scenario- specific challenges, and pathways to practical deployment[J]
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:03.344342Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation ef991feb-c054-4f39-96d1-9e71f2c1f166 · outbound
This paper cites Research on Feature Model and Mining Method for Current Transition Sequence[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Research on Feature Model and Mining Method for Current Transition Sequence[J]
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:03.089475Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation c786f34c-3026-482f-bb70-df9f9a4bb1aa · outbound
This paper cites A low -frequency residential NILM approach based on adaptive event detection[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series A low -frequency residential NILM approach based on adaptive event detection[J]
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:02.798815Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 83d5eab4-4894-430c-8df0-5fff55c41ac2 · outbound
This paper cites Unsupervised time series segmentation: A survey on recent advances[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unsupervised time series segmentation: A survey on recent advances[J]
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:02.627118Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation ddc5608a-77a2-42f3-ac9c-3cb100879c7d · outbound
This paper cites Adaptive algorithms for change point detection in financial time series[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Adaptive algorithms for change point detection in financial time series[J]
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:02.383770Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation efff6abe-9966-4f78-add6-67db853a86c8 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 33
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:02.173585Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 34464876-255c-43ff-aced-347fbb3fed5f · outbound
This paper cites CLaP -- State Detection from Time Series.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series CLaP -- State Detection from Time Series
Reference 34
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T00:53:57.225007Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 4a249aee-48e4-4caf-bd44-0fa411b69b37 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 35
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:01.781493Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 0e6ed634-70c0-4988-bae7-0db3cf672c60 · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 36
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:01.622833Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 0adec100-8dd5-4ca7-aad0-1c160cb619c3 · outbound
This paper cites Time2State: An unsupervised framework for inferring the latent states in time series data[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Time2State: An unsupervised framework for inferring the latent states in time series data[J]
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:01.404755Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 0e9c24cf-f3c8-4457-9c51-13fa91e473f6 · outbound
This paper cites Analyzing the performance of biomedical time-series segmentation with electrophysiology data[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Analyzing the performance of biomedical time-series segmentation with electrophysiology data[J]
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:01.053838Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 0db23c07-9762-4846-a2cb-3ff0ab5d1bad · outbound
This paper cites A residential labeled dataset for smart meter data analy tics[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series A residential labeled dataset for smart meter data analy tics[J]
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:00.748088Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 13553774-8ad4-4b79-af3c-48c4b8d6ffb6 · outbound
This paper cites Transient event detection algorithm for non-intrusive load monitoring[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Transient event detection algorithm for non-intrusive load monitoring[J]
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:00.497572Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 22262c26-6465-4e1a-8690-b687a63d8ac0 · outbound
This paper cites Nonintrusive load monitoring (NILM) using a deep learning model with a transformer-based attention mechanism and temporal pooling[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Nonintrusive load monitoring (NILM) using a deep learning model with a transformer-based attention mechanism and temporal pooling[J]
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:54:00.229975Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 3e174615-2c37-4631-bffe-896c82bb1205 · outbound
This paper cites Enhancing non-intrusive load monitoring through transfer learning with transformer models[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Enhancing non-intrusive load monitoring through transfer learning with transformer models[J]
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:53:59.939598Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 56ce09fa-7db9-4bab-adbf-77f2f6eefc34 · outbound
This paper cites Non-intrusive load monitoring model based on SimCLR and visualized color V-I trajectories[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Non-intrusive load monitoring model based on SimCLR and visualized color V-I trajectories[J]
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:53:59.678932Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation eff08559-3189-471e-bf9d-4593d8257a8f · outbound
This paper cites N., et a l.
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:53:59.416981Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 771ef5a6-b190-4d23-bd5c-922f9f667492 · outbound
This paper cites Non-intrusive load monitoring based on time-enhanced multidimensional feature visualization[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Non-intrusive load monitoring based on time-enhanced multidimensional feature visualization[J]
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:53:59.258538Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 0b1122a9-5f94-43b9-aaea-84f3e77213bf · outbound
This paper cites Change -point detection with deep learning: A review[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Change -point detection with deep learning: A review[J]
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:53:59.099901Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation d9ebd69a-292d-4c87-8d13-50fdfbf7976d · outbound
This paper cites Automatic change -point detection in time series via deep learning[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Automatic change -point detection in time series via deep learning[J]
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:53:58.919445Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 03fa9fbe-bdd1-42c5-89a7-f8ded1bc48fc · outbound
This paper cites Online neural ne tworks for change-point detection[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Online neural ne tworks for change-point detection[J]
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:53:58.705931Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation eea281fb-50e2-49f4-a2a8-6448d37333a1 · outbound
This paper cites Short-term power load forecasting based on Seq2Seq model integrating Bayesian optimization, temporal convolutional network and attention[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Short-term power load forecasting based on Seq2Seq model integrating Bayesian optimization, temporal convolutional network and attention[J]
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:53:58.483663Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation cbbcdea0-4921-416b-bd37-8f88ca99a09f · outbound
This paper cites A hybrid neural network based on Bayesian optimization for non-intrusive load disaggregation[C].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series A hybrid neural network based on Bayesian optimization for non-intrusive load disaggregation[C]
Reference 51
- Resolution
- verified exact
- raw_fallback, observed 2026-08-05T00:53:56.988538Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation aa7e05cc-9425-4088-983d-bb21d6e421bf · outbound
This paper cites R., KHALID S., et al.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series R., KHALID S., et al
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:53:58.283223Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 83b965b4-b5a2-4831-a636-4c5ab44401a6 · outbound
This paper cites Evaluation metrics and statistical tests for machine learning[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Evaluation metrics and statistical tests for machine learning[J]
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:53:58.160582Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 3a76b229-7824-4bb6-a249-4a9df2a799f3 · outbound
This paper cites A closer look at classification evaluation metrics and a critical reflection of common evaluation practice[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series A closer look at classification evaluation metrics and a critical reflection of common evaluation practice[J]
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:53:57.992275Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 4d8ada95-e42c-4f07-a00a-82d2ebe3209c · outbound
This paper cites An experimental evaluation of anomaly detection in time series[J].
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series An experimental evaluation of anomaly detection in time series[J]
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T00:53:57.747874Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation a863a53c-59c3-4343-bb6d-aa8ca3b18cad · outbound
This paper cites an unresolved cited work.
BayesSeg: A Bayesian Optimization Framework for State Segmentation of Electricity Consumption Time Series Unresolved cited work
Reference 2025
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T00:54:01.916409Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Pith citing papers
No inbound Pith citation observations are available.