Pith. sign in

Paper Citation Record · LEDGER

On Markov chain Monte Carlo methods for tall data

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1505.02827.

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

pith.paper-citation-record.v1
1505.02827 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 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:39:11.187935Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-14T18:29:22.691606Z

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 d407ac4c-e6a4-4a67-93bf-2ce33cb6835c · inbound

Mini-batch Metropolis-Hastings MCMC with Reversible SGLD Proposal cites this paper.

Mini-batch Metropolis-Hastings MCMC with Reversible SGLD Proposal On Markov chain Monte Carlo methods for tall data

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-14T14:39:11.187935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:39:11.187935Z digest=sha256:3ffd9c5c8cef2c2e0e7cee1277e8201a7f36a0a0fe1377dbf27bd227d54bafbf

Observation f9540beb-494c-473b-9862-43f6f5d264da · inbound

State-of-art minibatches via novel DPP kernels: discretization, wavelets, and rough objectives cites this paper.

State-of-art minibatches via novel DPP kernels: discretization, wavelets, and rough objectives On Markov chain Monte Carlo methods for tall data

Reference 257

Resolution
metadata mismatch
local_arxiv, observed 2026-05-14T18:29:22.695079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-14T18:27:47.980646Z digest=sha256:99151fe0848eeb4db0e879e991091ff8d7813d3b802332e0d5ad453def4ec72a