Paper Citation Record · LEDGER

Providing Machine Learning Potentials with High Quality Uncertainty Estimates

As of 20 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2501.05250.

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

pith.paper-citation-record.v1
2501.05250 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:18:35.812006Z

measured 35 of 35 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T15:40:31.329045Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

verified exact2
verified fuzzy18
unresolved14
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1bc5f946-d1a9-4509-a1af-c3e8fe722d1f · outbound

This paper cites an unresolved cited work.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:18:37.148466Z

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.

Observation 40fc139b-2cad-43f1-b013-0a35cb6c5df9 · outbound

This paper cites & Smit, B.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates & Smit, B

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:37.137039Z

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.

Observation f756c514-04a9-4da8-a869-19738213bc4c · outbound

This paper cites an unresolved cited work.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:18:37.125901Z

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.

Observation bad9e859-de5e-4b37-a0ad-603340356ea6 · outbound

This paper cites Practical Aspects of Computational Chemistry-Methods, Concepts & Applications (Springer, 2022).

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Practical Aspects of Computational Chemistry-Methods, Concepts & Applications (Springer, 2022)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:37.020699Z

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.

Observation ec316f32-4ea8-4b54-947b-27d314f5cd11 · outbound

This paper cites an unresolved cited work.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:18:37.009639Z

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.

Observation 807a23e4-9f33-469a-9f9b-784056330d92 · outbound

This paper cites & Stewart, J.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates & Stewart, J

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.998644Z

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.

Observation f92f0295-50d0-405f-bb0f-7ae9948165dc · outbound

This paper cites an unresolved cited work.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T21:18:35.403974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91420b93-d1a0-48de-9662-2359c94af325 · outbound

This paper cites an unresolved cited work.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:18:36.986328Z

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.

Observation 1da9de2a-1e43-4f87-842c-a8d3b775090d · outbound

This paper cites & Parrinello, M.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates & Parrinello, M

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T21:18:35.411297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90643c37-73c4-4edc-b5cd-bf3599070542 · outbound

This paper cites L., Shkurti, A., Bray, D.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates L., Shkurti, A., Bray, D

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.888298Z

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.

Observation b21e2bb3-0ed8-4fca-9cff-aeb3a144bfac · outbound

This paper cites P., Payne, M.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates P., Payne, M

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.875991Z

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.

Observation 310dc4fb-9869-42ca-883a-ffe7c5e8de12 · outbound

This paper cites an unresolved cited work.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:18:36.865266Z

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.

Observation 8f1552df-bdd6-4e0a-8b00-61ddaed279d0 · outbound

This paper cites C., Rohrer, J., Albe, K.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates C., Rohrer, J., Albe, K

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.792868Z

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.

Observation 8e11f32a-b98b-4ffb-8361-b8c06293ef69 · outbound

This paper cites S., Isayev, O.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates S., Isayev, O

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.729914Z

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.

Observation a18983a7-5826-4a20-9dcd-4c322a7a18d7 · outbound

This paper cites Four generations of high-dimensional neural network potentials.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Four generations of high-dimensional neural network potentials

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.717378Z

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.

Observation 11e85175-93af-4602-8e84-86c74189a098 · outbound

This paper cites T., Sauceda, H.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates T., Sauceda, H

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.672191Z

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.

Observation c089a827-9fe2-468e-8d1c-3f3c955db736 · outbound

This paper cites S., Nebgen, B., Lubbers, N., Isayev, O.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates S., Nebgen, B., Lubbers, N., Isayev, O

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.562254Z

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.

Observation 2e2b895f-7c79-4277-a6ba-d9221cbdefff · outbound

This paper cites & Tadmor, E.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates & Tadmor, E

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.550074Z

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.

Observation 55525708-af97-4070-becb-014127ab0da4 · outbound

This paper cites & Lucia, S.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates & Lucia, S

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.537489Z

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.

Observation 16291da9-b38b-4ff9-96c7-e992d0c107c4 · outbound

This paper cites an unresolved cited work.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:18:36.461139Z

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.

Observation 919d714a-2389-40ee-a6da-c753721d32f7 · outbound

This paper cites Uncertainty in Neural Networks: Approximately Bayesian Ensembling.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Uncertainty in Neural Networks: Approximately Bayesian Ensembling

Reference 21

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Source-reported events for the cited work

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Observation 124802f9-1735-44dc-826b-92e3f9ee7872 · outbound

This paper cites an unresolved cited work.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:18:36.378901Z

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.

Observation 4775807d-d2e2-4f44-a350-50d5dc5a800a · outbound

This paper cites Deep Neural Networks as Gaussian Processes.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Deep Neural Networks as Gaussian Processes

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T21:18:35.705048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63a9e85a-f8de-452b-b63c-1e077770d58b · outbound

This paper cites & Adams, R.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates & Adams, R

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.366428Z

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.

Observation 09eb758b-a126-4ab3-8f0f-72b256320904 · outbound

This paper cites TopSearch (2024).

Providing Machine Learning Potentials with High Quality Uncertainty Estimates TopSearch (2024)

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.282422Z

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.

Observation 490fd1a6-7f14-409d-bb0f-8078abb7b1b5 · outbound

This paper cites E., Jordan, K.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates E., Jordan, K

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.251949Z

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.

Observation e0d11427-3626-48ff-b6d3-cccd26fc1453 · outbound

This paper cites & Schulten, K.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates & Schulten, K

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.176135Z

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.

Observation 95f82549-a4cb-4397-bbef-ebbc4a7ef0b4 · outbound

This paper cites & Liu, T.-Y.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates & Liu, T.-Y

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.162084Z

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.

Observation 3b9683a8-2eed-4592-97ab-8a2fff169576 · outbound

This paper cites an unresolved cited work.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Unresolved cited work

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T21:18:35.774695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 855b511e-920c-429a-ba7a-a91ee5513d92 · outbound

This paper cites & Wierstra, D.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates & Wierstra, D

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:18:36.149105Z

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.

Observation b0ec9e0e-0122-457b-9a3f-42bf86e992a7 · outbound

This paper cites Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T21:18:35.783575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95864619-f5af-42df-9a5c-d06f73cbf86b · outbound

This paper cites & Subedar, M.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates & Subedar, M

Reference 32

Resolution: verified exact; doi, observed 2026-08-10T21:18:35.873020Z

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.

Observation 8bdd3339-4610-4b65-9d58-1f04a47bb3cd · outbound

This paper cites an unresolved cited work.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:18:36.081839Z

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.

Observation f65a8180-482b-494e-88d6-236385972b37 · outbound

This paper cites Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification.

Providing Machine Learning Potentials with High Quality Uncertainty Estimates Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-10T21:18:35.936656Z

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.

Pith citing papers

Observation 38d4c0a1-44d3-4853-89b7-eafcced4322e · inbound

Bayesian Neural Networks versus deep ensembles for uncertainty quantification in machine learning interatomic potentials cites this paper.

Bayesian Neural Networks versus deep ensembles for uncertainty quantification in machine learning interatomic potentials Providing Machine Learning Potentials with High Quality Uncertainty Estimates

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T15:40:31.329045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.