Paper Citation Record · LEDGER

On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2006.02409.

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

pith.paper-citation-record.v1
2006.02409 v4

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 2026-08-08T04:35:56.364437Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T17:23:09.961366Z

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 ce843ed4-2d72-486a-811c-91e6dedb548c · inbound

Scalable Thermodynamic Second-order Optimization cites this paper.

Scalable Thermodynamic Second-order Optimization On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-08T04:35:56.364437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 088e1fee-66f3-4f9c-8276-7ec45f5175c2 · inbound

On the Convergence Behavior of Preconditioned Gradient Descent Toward the Rich Learning Regime cites this paper.

On the Convergence Behavior of Preconditioned Gradient Descent Toward the Rich Learning Regime On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-16T17:23:09.963441Z

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 18df6967-6366-480e-a539-f26fcbd825a5 · inbound

Fast Gauss-Newton for Multiclass Cross-Entropy cites this paper.

Fast Gauss-Newton for Multiclass Cross-Entropy On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:46:09.647787Z

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 1869e1e6-8cd3-41db-a885-8f262af4c360 · inbound

Energy Manifold Natural Gradient Descent: Riemannian Optimization for Neural PDE Solvers cites this paper.

Energy Manifold Natural Gradient Descent: Riemannian Optimization for Neural PDE Solvers On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T06:09:01.509015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.