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Paper Citation Record · LEDGER

New Machine Learning Techniques for Simulation-Based Inference: InferoStatic Nets, Kernel Score Estimation, and Kernel Likelihood Ratio Estimation

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2210.01680.

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

pith.paper-citation-record.v1
2210.01680 v2

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 2026-08-14T06:32:32.682623+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T23:37:30.017773Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T05:29:33.240403Z

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 aab17975-0016-4a6b-b154-0ea6d17a8f25 · inbound

Optimizers for Stabilizing Likelihood-free Inference cites this paper.

Optimizers for Stabilizing Likelihood-free Inference New Machine Learning Techniques for Simulation-Based Inference: InferoStatic Nets, Kernel Score Estimation, and Kernel Likelihood Ratio Estimation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-09T23:37:30.017773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T23:37:30.017773Z digest=sha256:e5463bc002eec24d02d549c63b4be3b02ca0649e757a9259d101d3f2ada595cf

Observation 03902bbf-89b7-4c8b-9a8d-edd731bd1525 · inbound

Higgs Signal Strength Estimation with Machine Learning under Systematic Uncertainties cites this paper.

Higgs Signal Strength Estimation with Machine Learning under Systematic Uncertainties New Machine Learning Techniques for Simulation-Based Inference: InferoStatic Nets, Kernel Score Estimation, and Kernel Likelihood Ratio Estimation

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-05T13:28:03.673381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:28:03.673381Z digest=sha256:185d5fc693836fa74c9c7cd604b8439d264ce5f4cd4bde99622e438804b49870

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-05T05:29:33.245867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-05T05:29:30.507669Z digest=sha256:9b9168451c2ce5d0988cb60f3ae30f4f8ab5d1b2c3a6abede117792a9a86a033