Paper Citation Record · LEDGER

Learning Neural Event Functions for Ordinary Differential Equations

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2011.03902.

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

pith.paper-citation-record.v1
2011.03902 v4

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 2026-08-20T06:33:59.587034+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:41:45.344467Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:17:37.102691Z

Reference resolution

0 of 0 outbound references displayed

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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 16432055-4fc1-4821-af92-a6c706d42fcc · inbound

Training Stiff Neural Ordinary Differential Equations with Explicit Exponential Integration Methods cites this paper.

Training Stiff Neural Ordinary Differential Equations with Explicit Exponential Integration Methods Learning Neural Event Functions for Ordinary Differential Equations

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-12T04:41:45.344467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f040063-2110-454e-a63a-ae6f438fa703 · inbound

Model reduction of parametric ordinary differential equations via autoencoders: representation properties and convergence analysis cites this paper.

Model reduction of parametric ordinary differential equations via autoencoders: representation properties and convergence analysis Learning Neural Event Functions for Ordinary Differential Equations

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:56:26.610867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 54e649f7-7806-4a50-a432-b7f538a0b196 · inbound

RigidFormer: Learning Rigid Dynamics using Transformers cites this paper.

RigidFormer: Learning Rigid Dynamics using Transformers Learning Neural Event Functions for Ordinary Differential Equations

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:21:16.909561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e3193312-9e8a-4d10-9b1e-8ade95d06667 · inbound

Learning regime-dependent governing equations: A symbolic decision tree approach cites this paper.

Learning regime-dependent governing equations: A symbolic decision tree approach Learning Neural Event Functions for Ordinary Differential Equations

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-30T14:24:45.215377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 244aea98-729e-4459-863e-37448f95f871 · inbound

Reconstructing and forecasting disease trajectories of patients with Alzheimer's disease using routine data in resource-constrained settings cites this paper.

Reconstructing and forecasting disease trajectories of patients with Alzheimer's disease using routine data in resource-constrained settings Learning Neural Event Functions for Ordinary Differential Equations

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-07-02T19:07:18.334310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 644ffa42-9443-4118-8cb7-2afa537f8916 · inbound

Embedding Hybrid Systems into Continuous Latent Vector Fields cites this paper.

Embedding Hybrid Systems into Continuous Latent Vector Fields Learning Neural Event Functions for Ordinary Differential Equations

Reference 76

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T04:17:37.104515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.