Paper Citation Record · LEDGER

Deep Gaussian Mixture Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1711.06929.

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

pith.paper-citation-record.v1
1711.06929 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 2026-08-07T05:03:00.011127Z

measured 1 of 1 external citation measurements

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

Source: pith, 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

2
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 50e5fbb8-4779-47bb-8726-04a4174bdd30 · inbound

IntTrajSim: Trajectory Prediction for Simulating Multi-Vehicle driving at Signalized Intersections cites this paper.

IntTrajSim: Trajectory Prediction for Simulating Multi-Vehicle driving at Signalized Intersections Deep Gaussian Mixture Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T05:03:00.011127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 642f808f-4ed5-4086-a28a-694c80d6d378 · inbound

SHeRL-FL: When Representation Learning Meets Split Learning in Hierarchical Federated Learning cites this paper.

SHeRL-FL: When Representation Learning Meets Split Learning in Hierarchical Federated Learning Deep Gaussian Mixture Models

Reference 148

Resolution: unresolved; no resolver link, observed 2026-08-05T22:03:09.876233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83961629-be43-41ae-ae5c-5398f5dcc914 · inbound

CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters cites this paper.

CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters Deep Gaussian Mixture Models

Reference 85

Resolution: verified exact; local_arxiv, observed 2026-06-28T07:41:44.813694Z

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 1d562b6f-640e-4c6e-9d94-5926e60e32ee · inbound

CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters cites this paper.

CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters Deep Gaussian Mixture Models

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-02T12:30:44.173564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.