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Paper Citation Record · LEDGER

Federated scientific machine learning for approximating functions and solving differential equations with data heterogeneity

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.13141.

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

pith.paper-citation-record.v1
2410.13141 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:21:45.124955Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T23:21:50.345000Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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 6bdf4171-a035-4e3f-8939-ddc5a0b939a8 · inbound

Neural-operator element method: Efficient and scalable finite element method enabled by reusable neural operators cites this paper.

Neural-operator element method: Efficient and scalable finite element method enabled by reusable neural operators Federated scientific machine learning for approximating functions and solving differential equations with data heterogeneity

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:21:50.469980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T23:21:45.124955Z digest=sha256:30387db4117b2e38fde8dfb2363c07bf298bdb35c250b12f4ede3177a741f2e6

Observation 7f871c61-2f7a-4b5d-aaf4-a47de3c12872 · inbound

Design Criteria for SGD Preconditioners: Local Conditioning, Noise Floors, and Basin Stability cites this paper.

Design Criteria for SGD Preconditioners: Local Conditioning, Noise Floors, and Basin Stability Federated scientific machine learning for approximating functions and solving differential equations with data heterogeneity

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-03T20:34:08.794388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:34:08.794388Z digest=sha256:2b39da5a336d9d568f08996db759f5605b109e00232c3bfa77a82e000433474a