Paper Citation Record · LEDGER

Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters

As of 7 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2607.26422.

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

pith.paper-citation-record.v1
2607.26422 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T16:19:10.167367Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

13 of 13 outbound references displayed

verified exact5
verified fuzzy0
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0d269fd0-ebf4-4e64-8fa2-64347baf83ff · outbound

This paper cites an unresolved cited work.

Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T16:19:10.155724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6ca5100-bd0e-4171-b9e5-967bc571e277 · outbound

This paper cites This approach achieves high predictive accuracy while also providing analytical expressions that offer insight into the underlying physics of the interaction parameters.

Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters This approach achieves high predictive accuracy while also providing analytical expressions that offer insight into the underlying physics of the interaction parameters

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T16:19:10.097606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d05325a-752c-43f8-9901-78f6079b49d4 · outbound

This paper cites Bridging constrained random-phase approximation and linear response theory for computing Hubbard parameters.

Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters Bridging constrained random-phase approximation and linear response theory for computing Hubbard parameters

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T16:19:10.138537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d3ee46e-829b-471a-bc94-f5e9b3d6b7c5 · outbound

This paper cites A.; Yates, J.

Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters A.; Yates, J

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T16:19:10.161372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f2646b6-6653-476f-8d5c-951de4dbf4b3 · outbound

This paper cites (8) Reddy, I.

Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters (8) Reddy, I

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T16:19:10.167367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb4af7b8-9245-45b3-94f4-811977bbbd93 · outbound

This paper cites (49) Yang, W.; Timrov, I.; Aquilante, F.; Son, Y.-W.

Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters (49) Yang, W.; Timrov, I.; Aquilante, F.; Son, Y.-W

Reference 19

Resolution: verified exact; doi, observed 2026-08-01T16:24:24.131118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 83c643de-95bd-4859-b58f-bb3702a3451a · outbound

This paper cites (45) Yu, W.; Zhang, Z.; Wan, X.; Guo, H.; Gui, Q.; Peng, Y.; Li, Y.; Fu, W.; Lu, D.; Ye, Y.; Guo, Y.

Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters (45) Yu, W.; Zhang, Z.; Wan, X.; Guo, H.; Gui, Q.; Peng, Y.; Li, Y.; Fu, W.; Lu, D.; Ye, Y.; Guo, Y

Reference 180

Resolution: unresolved; no resolver link, observed 2026-08-01T16:19:10.122230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e25836e7-74af-457c-bde5-ce078875184d · outbound

This paper cites (64) Tomczak, J.

Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters (64) Tomczak, J

Reference 183

Resolution: verified exact; doi, observed 2026-08-01T16:24:23.989232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation fc1f96c2-d532-434e-851f-7f0c6791145e · outbound

This paper cites (31) Aryasetiawan, F.; Karlsson, K.; Jepsen, O.; Schönberger, U.

Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters (31) Aryasetiawan, F.; Karlsson, K.; Jepsen, O.; Schönberger, U

Reference 263

Resolution: verified exact; doi, observed 2026-08-01T16:24:24.285047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 48712d90-0c5e-489d-9493-f94a86a5345f · outbound

This paper cites 26 (15) Reddy, I.

Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters 26 (15) Reddy, I

Reference 286

Resolution: verified exact; doi, observed 2026-08-01T16:24:24.317865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3487d620-5e16-48ae-95de-9a39d1bc656d · outbound

This paper cites Efficient Iterative Schemes for Ab Initio Total-Energy Calculations Using a Plane-Wave Basis Set.

Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters Efficient Iterative Schemes for Ab Initio Total-Energy Calculations Using a Plane-Wave Basis Set

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-01T16:19:10.144728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42243e8c-cc66-4563-a305-8ca67d5b1b04 · outbound

This paper cites (50) Carta, A.; Timrov, I.; Beck, S.; Ederer, C.

Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters (50) Carta, A.; Timrov, I.; Beck, S.; Ederer, C

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-01T16:19:10.133525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9acf9a71-d3ab-4956-838e-d853723137ec · outbound

This paper cites (13) Di Sante, D.; Kim, B.; Hanke, W.; Wehling, T.; Franchini, C.; Thomale, R.; Sangiovanni, G.

Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters (13) Di Sante, D.; Kim, B.; Hanke, W.; Wehling, T.; Franchini, C.; Thomale, R.; Sangiovanni, G

Reference 2395

Resolution: verified exact; doi, observed 2026-08-01T16:24:24.388869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

No inbound Pith citation observations are available.