Pith. sign in

Paper Citation Record · LEDGER

Numerical Study of a Particle Method for Gradient Flows

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1512.03029.

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

pith.paper-citation-record.v1
1512.03029 v3

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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:01:57.500905Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T11:40:59.379876Z

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 1a5cb749-21b9-4981-b55e-c9a217fe537c · inbound

Convergence of a particle method for gradient flows on the $L^p$-Wasserstein space cites this paper.

Convergence of a particle method for gradient flows on the $L^p$-Wasserstein space Numerical Study of a Particle Method for Gradient Flows

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-10T22:01:57.500905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:01:57.500905Z digest=sha256:ad6b52356e12442d3fc0274b2a685f7e9ca7e44deab77f7d200ab2a5993c70cc

Observation a6b96078-56e3-4000-a978-b5c01f56a8e9 · inbound

Machine-Learned Sampling of Conditioned Path Measures cites this paper.

Machine-Learned Sampling of Conditioned Path Measures Numerical Study of a Particle Method for Gradient Flows

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:40:59.415938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T11:40:57.516142Z digest=sha256:d93d1f3e7ed35b54c264d4208644545c2304bdb19979655fcc0edd41288adcbd