Paper Citation Record · LEDGER

Every Model Learned by Gradient Descent Is Approximately a Kernel Machine

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2012.00152.

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

pith.paper-citation-record.v1
2012.00152 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:19:06.882525Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, 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

49
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 030de9a1-7961-41b9-8eaa-ee99351fa5a5 · inbound

Adaptive kernel predictors from feature-learning infinite limits of neural networks cites this paper.

Adaptive kernel predictors from feature-learning infinite limits of neural networks Every Model Learned by Gradient Descent Is Approximately a Kernel Machine

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T11:19:06.882525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3e13189-06a8-48dc-9696-ea013b7eab41 · inbound

Random at First, Fast at Last: NTK-Guided Fourier Pre-Processing for Tabular DL cites this paper.

Random at First, Fast at Last: NTK-Guided Fourier Pre-Processing for Tabular DL Every Model Learned by Gradient Descent Is Approximately a Kernel Machine

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T11:29:47.506391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35810274-a53c-4db5-aede-d19bcf7de366 · inbound

A renormalization-group inspired lattice-based framework for piecewise generalized linear models cites this paper.

A renormalization-group inspired lattice-based framework for piecewise generalized linear models Every Model Learned by Gradient Descent Is Approximately a Kernel Machine

Reference 165

Resolution: verified exact; arxiv_id, observed 2026-05-08T20:59:11.447711Z

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.

Observation 109601aa-21b2-4cd7-956f-959f3ad8ef68 · inbound

Second-Order Path Kernel Interpolation Formulas in Machine Learning cites this paper.

Second-Order Path Kernel Interpolation Formulas in Machine Learning Every Model Learned by Gradient Descent Is Approximately a Kernel Machine

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:47:10.339182Z

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.