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Paper Citation Record · LEDGER

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort?

As of 20 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2501.05000.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.05000 v5

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:26:00.705100Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

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  • verified fuzzy5
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External citation measurements

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Outbound references

Observation ec75c19d-db05-432b-8e28-25eb3059aa03 · outbound

This paper cites doi:10.2833/9937.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? doi:10.2833/9937

Reference 1

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Observation 92426d35-4542-45a5-8523-d9d87cacf58a · outbound

This paper cites Ponnaganti, R.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Ponnaganti, R

Reference 2

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Observation f7c405b2-266c-4c6d-939f-844ded9ecf95 · outbound

This paper cites Van Der Stelt, T.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Van Der Stelt, T

Reference 3

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Observation b3bb76c7-760e-4105-b1cc-39efc8ee842f · outbound

This paper cites Mariano-Hern´ andez, L.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Mariano-Hern´ andez, L

Reference 4

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Observation 3dee663e-1666-44bd-8bdf-71df58675f06 · outbound

This paper cites Srithapon, D.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Srithapon, D

Reference 5

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Observation 999c15ea-d0aa-4825-8f5b-882dbb4524db · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 6

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Observation b3f9b785-d1b8-4440-8e8a-afcdb3ff34fd · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 7

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Observation 1e81b8db-16ce-44d6-8d05-668ae152afb4 · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 8

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Observation 6226d691-5659-4f8b-a3d2-6518927bdc1e · outbound

This paper cites Royal, S.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Royal, S

Reference 9

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Observation e9ce2645-8a92-40b5-8219-ab445994d14c · outbound

This paper cites Peterssen, M.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Peterssen, M

Reference 10

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Observation 3a6a1ce4-b104-41c2-a85e-bb1172eeeaae · outbound

This paper cites Wazirali, E.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Wazirali, E

Reference 11

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Observation ca11f35b-8d81-4a2d-badc-15d0873732ec · outbound

This paper cites Seiler, L.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Seiler, L

Reference 12

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Observation c898f15f-6bb0-4a22-b111-efedd5db3a05 · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 13

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Observation 6d0e07ab-5c57-4797-b556-a5fb22617ce6 · outbound

This paper cites Pallonetto, C.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Pallonetto, C

Reference 14

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Observation 7abcdc0d-74d1-4fd8-bf54-65080debabc9 · outbound

This paper cites Semmelmann, M.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Semmelmann, M

Reference 15

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Observation 330519d2-ca19-4db5-8b8d-a2b9b7524cab · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 16

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Observation f56a0a0c-85ee-41a8-a019-edd50748fa4f · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 17

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Observation f06293e5-b5b0-421c-b977-2385dce0b9c0 · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 18

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Observation efac9097-ccd4-47ed-8ced-1ce1c3769a56 · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 19

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Observation 86402615-7a6b-4f8c-ac66-d65ec921aa74 · outbound

This paper cites L’Heureux, K.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? L’Heureux, K

Reference 20

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Observation 5596d90d-657f-4f3b-824c-94de7e69d335 · outbound

This paper cites xLSTM: Extended Long Short-Term Memory.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? xLSTM: Extended Long Short-Term Memory

Reference 21

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Observation ccbf2a7e-8b2f-4402-8432-24d1f22a79e0 · outbound

This paper cites Kraus, F.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Kraus, F

Reference 22

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Observation 00403884-50cf-4459-aebc-7a159a78577e · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 23

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Observation fbe297b8-686f-4774-813b-b39a974bb9a9 · outbound

This paper cites Ribeiro, K.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Ribeiro, K

Reference 24

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Observation 08b61f4a-e71f-491d-b204-d98b21f6ad7e · outbound

This paper cites Improve Load Forecasting in Energy Communities through Transfer Learning using Open-Access Synthetic Profiles.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Improve Load Forecasting in Energy Communities through Transfer Learning using Open-Access Synthetic Profiles

Reference 25

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Observation 1f54972b-9841-4706-a991-95a230240cf5 · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 26

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Observation 98c95fd7-66af-4b01-9f21-752f17f0834a · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 27

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Observation fced5cb3-6317-4ee7-9f43-29aad4421bf1 · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 28

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Observation 576e14d6-dece-47bf-8e5e-405943ce411a · outbound

This paper cites URL https://data.london.gov.uk/dataset/ smartmeter-energy-use-data-in-london-households 33.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? URL https://data.london.gov.uk/dataset/ smartmeter-energy-use-data-in-london-households 33

Reference 29

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Observation eeec5b7c-aa87-4d60-b5a6-3b5f84dc7544 · outbound

This paper cites Ceruti, B.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Ceruti, B

Reference 30

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Observation 0b64a835-a520-48e4-9485-402fef308509 · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 31

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Observation c55f19fb-6d45-49cd-accb-2572481155e6 · outbound

This paper cites Ziel, Modeling public holidays in load forecasting: a german case study, Journal of Modern Power Systems and Clean Energy 6 (2) (2018) 191–207.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Ziel, Modeling public holidays in load forecasting: a german case study, Journal of Modern Power Systems and Clean Energy 6 (2) (2018) 191–207

Reference 32

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Observation 7a303f01-7bb1-4f63-b538-3e95733cdf77 · outbound

This paper cites A Time Series is Worth 64 Words: Long-term Forecasting with Transformers.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 33

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Observation 1fe400b8-e48d-4fa1-8018-27408ceffc4c · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 34

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Observation ebf6cd8b-0357-4141-8924-074ced95585f · outbound

This paper cites Van Rossum, F.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Van Rossum, F

Reference 35

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Observation 17f3b562-ede2-4dfc-bad2-4354a3672eae · outbound

This paper cites Ansel, E.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Ansel, E

Reference 36

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source=pdf_text observed=2026-08-10T21:26:00.688106Z digest=sha256:c2890921978a019b5b987464668f86af3f0cce76eba71cd485eee4ce3b5f63c9

Observation a817b5a2-6b1e-4473-9f5b-aa993af061a8 · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation add7494d-bba7-4930-9871-c28dff3db6cd · outbound

This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 38

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 237bf1a3-d258-4b07-9bdf-a5ecfdbbf188 · outbound

This paper cites URL https://www.exaa.at/.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? URL https://www.exaa.at/

Reference 39

Resolution
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Source-reported events for the cited work

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Observation 8de0f29d-a008-49d1-a323-53c89d05447a · outbound

This paper cites Barbour, D.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Barbour, D

Reference 40

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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This paper cites an unresolved cited work.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Unresolved cited work

Reference 41

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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This paper cites Wohlgenannt, G.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Wohlgenannt, G

Reference 42

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 7a82782a-197a-4439-96bf-797c2d3c43ff · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort? Adam: A Method for Stochastic Optimization

Reference 2015

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.