Paper Citation Record · LEDGER

Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1812.09764.

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

pith.paper-citation-record.v1
1812.09764 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:39:05.063555Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T07:59:39.625974Z

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 dc88f46f-175d-446a-8e2e-88ae768e1e41 · inbound

Topological Uncertainty for Anomaly Detection in the Neural-network EoS Inference with Neutron Star Data cites this paper.

Topological Uncertainty for Anomaly Detection in the Neural-network EoS Inference with Neutron Star Data Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-05T15:39:05.063555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca22721c-8ec1-4160-9a3c-c54cc0894c7d · inbound

Geometric Analysis of Neural Regression Collapse via Intrinsic Dimension cites this paper.

Geometric Analysis of Neural Regression Collapse via Intrinsic Dimension Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-18T10:22:33.238566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5df84db9-fee6-4bb2-a99f-6f5ee434394f · inbound

Scene Generation at Absolute Scale: Utilizing Semantic and Geometric Guidance From Text for Accurate and Interpretable 3D Indoor Scene Generation cites this paper.

Scene Generation at Absolute Scale: Utilizing Semantic and Geometric Guidance From Text for Accurate and Interpretable 3D Indoor Scene Generation Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-14T21:37:04.895721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff0f1d6f-d452-47f2-bc97-ba588875cfdf · inbound

Motif-based filtrations for persistent homology: A framework for graph isomorphism and property prediction cites this paper.

Motif-based filtrations for persistent homology: A framework for graph isomorphism and property prediction Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:48:02.057487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1ec09933-8840-4c4a-b2f7-6248d5106d66 · inbound

TopoGeoScore: A Self-Supervised Source-Only Geometric Framework for OOD Checkpoint Selection cites this paper.

TopoGeoScore: A Self-Supervised Source-Only Geometric Framework for OOD Checkpoint Selection Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:26:24.521713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3e94c990-fd98-469f-8af8-f7992c0ca549 · inbound

HodgeCover: Higher-Order Topological Coverage Drives Compression of Sparse Mixture-of-Experts cites this paper.

HodgeCover: Higher-Order Topological Coverage Drives Compression of Sparse Mixture-of-Experts Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:55:04.784943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 652072d7-51d5-4bc8-893c-a88367280f22 · inbound

A Three Axis Evaluation Framework for Mapper Algorithms cites this paper.

A Three Axis Evaluation Framework for Mapper Algorithms Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-07-04T07:59:39.627531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.