Paper Citation Record · LEDGER

Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2002.08860.

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

pith.paper-citation-record.v1
2002.08860 v3

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 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:11:42.993127Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T02:09:22.478346Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 5536a2bf-561f-49f0-a01a-b1c951e88fac · inbound

Learning mechanical systems from real-world data using discrete forced Lagrangian dynamics cites this paper.

Learning mechanical systems from real-world data using discrete forced Lagrangian dynamics Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:11:42.993127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a32303f1-1f95-4495-96a6-6db14c982789 · inbound

NEXUS: Neural Energy Fields for Physically Consistent Contact-Rich 3D Object Dynamics cites this paper.

NEXUS: Neural Energy Fields for Physically Consistent Contact-Rich 3D Object Dynamics Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-07-03T17:18:43.380156Z

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 59527680-9a79-40ef-88ef-e30d33de6756 · inbound

Locally Stable Neural ODEs with Characterized Region of Attraction cites this paper.

Locally Stable Neural ODEs with Characterized Region of Attraction Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-04T02:09:22.479901Z

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 9981f500-4ed4-433f-b1f2-b8788cf91475 · inbound

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts cites this paper.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-02T08:18:18.726803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a00f68bd-b6a3-4bcc-b451-34bc7f4ee058 · inbound

Learning the Brain's Dynamics as a Port-Hamiltonian System: A GNN-Surrogate Metriplectic Twin for Non-Equilibrium Cortical Dynamics and Closed-Loop Neuromodulation cites this paper.

Learning the Brain's Dynamics as a Port-Hamiltonian System: A GNN-Surrogate Metriplectic Twin for Non-Equilibrium Cortical Dynamics and Closed-Loop Neuromodulation Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-14T11:44:50.475874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1359e23-29f6-4dbd-b0b6-1b0c9a549d54 · inbound

Quantum Port-Hamiltonian Neural Networks: Learning Conservative and Dissipative Dynamics via Measurement-Induced Nonlinearity cites this paper.

Quantum Port-Hamiltonian Neural Networks: Learning Conservative and Dissipative Dynamics via Measurement-Induced Nonlinearity Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T06:43:05.226255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.