Pith. sign in

Paper Citation Record · LEDGER

Bayesian neural networks for weak solution of PDEs with uncertainty quantification

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2101.04879.

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

pith.paper-citation-record.v1
2101.04879 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 2026-08-08T16:20:51.037441Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

17
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation cd87a6ff-22e7-4840-a5a5-c7bdb4eeed7f · inbound

DGenNO: A Novel Physics-aware Neural Operator for Solving Forward and Inverse PDE Problems based on Deep, Generative Probabilistic Modeling cites this paper.

DGenNO: A Novel Physics-aware Neural Operator for Solving Forward and Inverse PDE Problems based on Deep, Generative Probabilistic Modeling Bayesian neural networks for weak solution of PDEs with uncertainty quantification

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-08T16:20:51.037441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T16:20:51.037441Z digest=sha256:b93f08f3b8a71aad39d3b738a7ab9701a47a921fded2c4bb7622ddb31ef879b6

Observation 03954270-2099-476a-a5d1-d1690449be53 · inbound

Materials Behavior as Mechanism Ensembles: A Probabilistic Framework for Emergent Behaviors cites this paper.

Materials Behavior as Mechanism Ensembles: A Probabilistic Framework for Emergent Behaviors Bayesian neural networks for weak solution of PDEs with uncertainty quantification

Reference 114

Resolution
verified exact
local_arxiv, observed 2026-07-30T10:35:57.623920Z

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=pdf_text observed=2026-07-30T10:34:56.774742Z digest=sha256:ad0d62680ec0732052b212bdc2fab635f621eb3d5bdbc193ff0b8eb4ef285a29