Paper Citation Record · LEDGER

Can machines learn density functionals? Past, present, and future of ML in DFT

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2503.01709.

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

pith.paper-citation-record.v1
2503.01709 v1

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:51:21.379200Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T16:35:49.937716Z

Reference resolution

0 of 0 outbound references displayed

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verified fuzzy0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation df1dc60c-437e-428d-b2ba-cd5b1b894102 · inbound

Machine learning potentials for modeling alloys across compositions cites this paper.

Machine learning potentials for modeling alloys across compositions Can machines learn density functionals? Past, present, and future of ML in DFT

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-07T00:51:21.379200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e452cdcf-c5e4-474b-b947-7f79889e3624 · inbound

Accurate and scalable exchange-correlation with deep learning cites this paper.

Accurate and scalable exchange-correlation with deep learning Can machines learn density functionals? Past, present, and future of ML in DFT

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:07:13.990089Z

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 3bdf0491-6d1c-46a7-8af5-29adf812da20 · inbound

Overfitting by design: neural network density functionals for water cites this paper.

Overfitting by design: neural network density functionals for water Can machines learn density functionals? Past, present, and future of ML in DFT

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:41:45.214707Z

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 3049423d-3dc6-4559-9cd3-0ed574e6d23e · inbound

Quantum statistical mechanics: Gauge invariance, operator shifting, hyperdensity functionals, and nonequilibrium sum rules cites this paper.

Quantum statistical mechanics: Gauge invariance, operator shifting, hyperdensity functionals, and nonequilibrium sum rules Can machines learn density functionals? Past, present, and future of ML in DFT

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-07-01T16:35:49.955067Z

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 c57caf55-54cd-444c-9708-f60a383e60c7 · inbound

Quantum statistical mechanics: Gauge invariance, operator shifting, hyperdensity functionals, and nonequilibrium sum rules cites this paper.

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-02T13:19:03.108644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa6fbb8c-4ed2-4d06-90fc-99b87b06c73b · inbound

ML and AI for density functional theory: different priorities for Kohn-Sham and orbital-free DFT, for electronic and nuclear DFT cites this paper.

ML and AI for density functional theory: different priorities for Kohn-Sham and orbital-free DFT, for electronic and nuclear DFT Can machines learn density functionals? Past, present, and future of ML in DFT

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-11T21:44:37.034392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd4802a1-ea9d-4317-9b40-cb329ffdb4ce · inbound

Future directions in nuclear $\beta$ decay at FRIB and beyond cites this paper.

Future directions in nuclear $\beta$ decay at FRIB and beyond Can machines learn density functionals? Past, present, and future of ML in DFT

Reference 190

Resolution: unresolved; no resolver link, observed 2026-08-01T04:00:59.105169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.