Pith. sign in

Paper Citation Record · LEDGER

Bayesian Learning via Neural Schr\"odinger-F\"ollmer Flows

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2111.10510.

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

pith.paper-citation-record.v1
2111.10510 v9

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:44:35.597156Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T00:19:46.628629Z

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 723cb7fe-7c31-49b0-951c-fe2d699d9cf5 · inbound

No Trick, No Treat: Pursuits and Challenges Towards Simulation-free Training of Neural Samplers cites this paper.

No Trick, No Treat: Pursuits and Challenges Towards Simulation-free Training of Neural Samplers Bayesian Learning via Neural Schr\"odinger-F\"ollmer Flows

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-08T14:44:35.597156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T14:44:35.597156Z digest=sha256:bd3b7c4d9f4ccfc8a7a6f4a4ddc8611f9faf20abef66519ea0114fef983aa004

Observation 0d689ce5-5c43-4a33-ab78-edf3872d92f4 · inbound

Path Integral Optimiser: Global Optimisation via Neural Schr\"odinger-F\"ollmer Diffusion cites this paper.

Path Integral Optimiser: Global Optimisation via Neural Schr\"odinger-F\"ollmer Diffusion Bayesian Learning via Neural Schr\"odinger-F\"ollmer Flows

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T05:58:16.165486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:58:16.165486Z digest=sha256:c697e710c91cf4fed8cc23551af4aa50cb54b40520faccfbbc394e00696c425c

Observation 3c7ae0be-605e-4ae0-936e-01019a240bf4 · inbound

Annealed Langevin Monte Carlo for Flow ODE Sampling cites this paper.

Annealed Langevin Monte Carlo for Flow ODE Sampling Bayesian Learning via Neural Schr\"odinger-F\"ollmer Flows

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:19:46.630031Z

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=arxiv_source observed=2026-05-10T00:19:20.706229Z digest=sha256:9dc74156168748c34ca0659ab01afaafe7ac95e618f1d122e5ea17a498868c62