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Paper Citation Record · LEDGER

HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.04832.

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

pith.paper-citation-record.v1
2310.04832 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:35:28.258906Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T20:35:28.911150Z

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 66cbf68f-81a3-49c8-a003-5bb9b2781ca7 · inbound

Extracting a stochastic model for predator-prey dynamic of turbulence and zonal flows with limited data cites this paper.

Extracting a stochastic model for predator-prey dynamic of turbulence and zonal flows with limited data HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-05T20:35:28.964371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T20:35:28.258906Z digest=sha256:a9abae6d0f3eabf4956bc69d38ba8a659e8f1a4e5c681799f57cb949f1eb68d8

Observation 1a1eac8b-b534-46dd-8055-b76803476083 · inbound

Neural operator discovery from heterogeneous trajectories cites this paper.

Neural operator discovery from heterogeneous trajectories HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations

Reference 2

Resolution
unresolved
no resolver link, observed 2026-07-31T23:47:25.776267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T23:47:25.776267Z digest=sha256:1bf957e8d48ba8f1526bf132c814eb28782e398c3340a739ea0b3428b7b468f4