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Paper Citation Record · LEDGER

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search

As of 18 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2502.01527.

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

pith.paper-citation-record.v1
2502.01527 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:05:33.591626Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

30 of 30 outbound references displayed

  • verified exact0
  • verified fuzzy28
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 148cac93-dca4-4a5b-95e4-51f94c60c45b · outbound

This paper cites Applied Soft Com- puting 64, 366–376 (Mar 2018).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Applied Soft Com- puting 64, 366–376 (Mar 2018)

Reference 1

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f91dfe4c-d777-40d9-841b-6db9b89cb5cc · outbound

This paper cites Energy Conversion and Management252, 115047 (Jan 2022).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Energy Conversion and Management252, 115047 (Jan 2022)

Reference 2

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 61ef18f6-4a06-4d7b-950f-267a63e9582a · outbound

This paper cites Nature Communications13(1) (Oct 2022).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Nature Communications13(1) (Oct 2022)

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation eb6310a8-ba6e-49c6-95c6-08289a67dd8a · outbound

This paper cites an unresolved cited work.

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Unresolved cited work

Reference 4

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0afcb6bb-3426-4217-9aea-38b58c01880e · outbound

This paper cites Journal of Machine Learning Research3(Nov), 507–554 (2002).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Journal of Machine Learning Research3(Nov), 507–554 (2002)

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9b428026-4f1f-4730-8558-52ee02dc9bb5 · outbound

This paper cites Chapman and Hall/CRC (Sep 2018).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Chapman and Hall/CRC (Sep 2018)

Reference 6

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7fa8d95a-8350-4475-b9f4-c277e882e126 · outbound

This paper cites Data Mining and Knowledge Discovery22(1), 106–148 (Jan 2011).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Data Mining and Knowledge Discovery22(1), 106–148 (Jan 2011)

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 064f8c97-2d30-455c-80f6-35f2529da0da · outbound

This paper cites Machine Learning20(3), 197–243 (Sep 1995).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Machine Learning20(3), 197–243 (Sep 1995)

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9a2b854a-b732-479a-9e1a-01f8059a7ec2 · outbound

This paper cites MIT Press, Cam- bridge, MA (1960).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search MIT Press, Cam- bridge, MA (1960)

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 3c511e70-bb8b-4a0c-83be-7545de69da57 · outbound

This paper cites Springer New York, 2nd edn.

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Springer New York, 2nd edn

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 21a0cdb3-ebad-4377-88f2-065d693693c3 · outbound

This paper cites Communica- tions Physics 3(1) (May 2020) 12 JD.

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Communica- tions Physics 3(1) (May 2020) 12 JD

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation fcc9fec6-0ab0-4dd7-a9cc-b92c0203d1e6 · outbound

This paper cites Springer Publishing Company, 2nd edn.

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Springer Publishing Company, 2nd edn

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation b81d300b-8d21-4862-8ce2-ee27fd0e15e6 · outbound

This paper cites an unresolved cited work.

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Unresolved cited work

Reference 13

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8eabe46d-0fd5-4717-b69f-87ceb9c0a030 · outbound

This paper cites The MIT Press (2009).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search The MIT Press (2009)

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8b6cd9bb-6452-4e89-bb69-1e85adaed21b · outbound

This paper cites IEEE Robotics and Automation Letters5(2), 3715–3722 (Apr 2020).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search IEEE Robotics and Automation Letters5(2), 3715–3722 (Apr 2020)

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:05:33.837284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f1e23baa-d37c-472d-a0cd-d14cbd9b7606 · outbound

This paper cites In: Pan, S.J., Sugiyama, M.

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search In: Pan, S.J., Sugiyama, M

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-09T15:05:33.823716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f7db3210-f7dd-4d67-b343-cba4780dcdc1 · outbound

This paper cites In: Kratochvíl, V., Studený, M.

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search In: Kratochvíl, V., Studený, M

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-09T15:05:33.809718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 966e5bf3-646c-4250-bd9f-17318b1b2f9b · outbound

This paper cites Artificial Intelligence in Medicine 107, 101912 (Jul 2020).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Artificial Intelligence in Medicine 107, 101912 (Jul 2020)

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 99d6ba0d-9569-4275-83ca-fb4daa6f52e1 · outbound

This paper cites IEEE Transactions on Intelligent Transportation Systems 23(7), 6766–6773 (Jul 2022).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search IEEE Transactions on Intelligent Transportation Systems 23(7), 6766–6773 (Jul 2022)

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 50b4cbe8-9aba-42e1-914f-37fc8b967462 · outbound

This paper cites IEEE Transactions on Computational Intelligence and AI in Games7(4), 347–360 (Dec 2015).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search IEEE Transactions on Computational Intelligence and AI in Games7(4), 347–360 (Dec 2015)

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5e32c6c0-b111-4299-b3ad-385b0c5c6d42 · outbound

This paper cites International Journal of Data Science and Analytics3, 121 – 129 (2017).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search International Journal of Data Science and Analytics3, 121 – 129 (2017)

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f9aca786-0dee-48f8-be56-c04273603ee7 · outbound

This paper cites Progress in Artificial Intelligence8(4), 425–439 (May 2019).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Progress in Artificial Intelligence8(4), 425–439 (May 2019)

Reference 22

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raw_fallback, observed 2026-08-09T15:05:33.741001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 26335d0b-040e-4bac-b9ae-3836cca065f5 · outbound

This paper cites Journal of Statistical Software 35(3), 1–22 (2010).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Journal of Statistical Software 35(3), 1–22 (2010)

Reference 23

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raw_fallback, observed 2026-08-09T15:05:33.728409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 1779ac2e-8bf1-4a87-9417-73521ef9742f · outbound

This paper cites Forest Ecology and Management457, 117723 (Feb 2020).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Forest Ecology and Management457, 117723 (Feb 2020)

Reference 24

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raw_fallback, observed 2026-08-09T15:05:33.715447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e6143f8e-bf84-4a35-8dcc-530531867c69 · outbound

This paper cites Nature529(7587), 484–489 (Jan 2016).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Nature529(7587), 484–489 (Jan 2016)

Reference 25

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raw_fallback, observed 2026-08-09T15:05:33.701284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 11680d04-caaa-44fa-95ff-5c5382d23f15 · outbound

This paper cites Science362(6419), 1140–1144 (Dec 2018).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Science362(6419), 1140–1144 (Dec 2018)

Reference 26

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raw_fallback, observed 2026-08-09T15:05:33.686103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 08b623a8-6323-4ce6-8b98-1c9b165c0fc7 · outbound

This paper cites Springer- Verlag, New York, USA (1993).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Springer- Verlag, New York, USA (1993)

Reference 27

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raw_fallback, observed 2026-08-09T15:05:33.671557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T15:05:33.578711Z digest=sha256:36c14c6cda394dc8d3d27281a99d09807cb3b8ca7a9e79c54bf2f95847777a6b

Observation 3d23041e-6353-4e65-9790-04a228c46e27 · outbound

This paper cites IEEE Transac- tions on Intelligent Transportation Systems22(2), 1185–1195 (Feb 2021) Enhancing BN Structural Learning with MCTS 13.

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search IEEE Transac- tions on Intelligent Transportation Systems22(2), 1185–1195 (Feb 2021) Enhancing BN Structural Learning with MCTS 13

Reference 28

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raw_fallback, observed 2026-08-09T15:05:33.657156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 107893c6-5dc0-4d09-bd4e-3da5cff1d94b · outbound

This paper cites Journal of Ambient Intelligence and Humanized Computing14(9), 12789–12805 (Jul 2022).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Journal of Ambient Intelligence and Humanized Computing14(9), 12789–12805 (Jul 2022)

Reference 29

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raw_fallback, observed 2026-08-09T15:05:33.642452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4ee070eb-7e50-45cf-8026-f4e03955e13c · outbound

This paper cites Artificial Intelligence Review 56(3), 2497–2562 (Jul 2022).

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Artificial Intelligence Review 56(3), 2497–2562 (Jul 2022)

Reference 30

Resolution
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raw_fallback, observed 2026-08-09T15:05:33.626435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Pith citing papers

No inbound Pith citation observations are available.