Paper Citation Record · LEDGER

Deep Learning of Multivariate Extremes via a Geometric Representation

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2406.19936.

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

pith.paper-citation-record.v1
2406.19936 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:58:33.025134Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T00:46:24.676698Z

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 98048f1c-c7af-482a-99a1-ddb0b0e3042b · inbound

Piecewise-linear modeling of multivariate geometric extremes cites this paper.

Piecewise-linear modeling of multivariate geometric extremes Deep Learning of Multivariate Extremes via a Geometric Representation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T20:58:33.025134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 677acfb7-067c-447b-ac37-f8bbcb7e5c98 · inbound

MOPED: A moving sum method for change point detection in pairwise extremal dependence cites this paper.

MOPED: A moving sum method for change point detection in pairwise extremal dependence Deep Learning of Multivariate Extremes via a Geometric Representation

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-05T13:32:23.943982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f479ec62-cda7-402f-a48c-1f9ee9edcc52 · inbound

Exploring climate change effects on concurrent floods and concurrent droughts via statistical deep learning cites this paper.

Exploring climate change effects on concurrent floods and concurrent droughts via statistical deep learning Deep Learning of Multivariate Extremes via a Geometric Representation

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:51:09.041429Z

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.

Observation 8534e911-999b-4e0b-9cf9-cf1b76c3a5b2 · inbound

Extrapolation in Statistical Learning with Extreme Value Theory cites this paper.

Extrapolation in Statistical Learning with Extreme Value Theory Deep Learning of Multivariate Extremes via a Geometric Representation

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:31:09.428137Z

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.

Observation fb49035f-f568-466d-a0e8-b70bb2c1f048 · inbound

Diagnostic Tools for Extreme Value Regression Models cites this paper.

Diagnostic Tools for Extreme Value Regression Models Deep Learning of Multivariate Extremes via a Geometric Representation

Reference 53

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T00:46:24.679284Z

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.

Observation ea3b2b33-b847-4522-b36c-6d7a5e6818ee · inbound

Flood risk estimation via geometric extremal graphical models cites this paper.

Flood risk estimation via geometric extremal graphical models Deep Learning of Multivariate Extremes via a Geometric Representation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T00:34:06.053499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.