Paper Citation Record · LEDGER

Hamiltonian Generative Networks

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:1909.13789.

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

pith.paper-citation-record.v1
1909.13789 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:57:32.179936Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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External citation measurements

29
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 664d9c42-e46c-4d42-b680-541a1cb86541 · inbound

Reinforcement Learning Closures for Underresolved Partial Differential Equations using Synthetic Data cites this paper.

Reinforcement Learning Closures for Underresolved Partial Differential Equations using Synthetic Data Hamiltonian Generative Networks

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T20:57:32.179936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 357d7999-0fa4-4cbf-b11c-3bb73496695a · inbound

KITINet: Kinetics Theory Inspired Network Architectures with PDE Simulation Approaches cites this paper.

KITINet: Kinetics Theory Inspired Network Architectures with PDE Simulation Approaches Hamiltonian Generative Networks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:33.400067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b987e41-7265-481e-bf90-4022177d76e8 · inbound

Learning long range dependencies through time reversal symmetry breaking cites this paper.

Learning long range dependencies through time reversal symmetry breaking Hamiltonian Generative Networks

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T10:29:46.467599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57898daa-cac2-4dfc-9f60-0e587431be6f · inbound

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network cites this paper.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Hamiltonian Generative Networks

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T16:10:27.493692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6577552-5d2e-4a62-b650-ea2f05cc20dc · inbound

Differential-Integral Neural Operator for Long-Term Turbulence Forecasting cites this paper.

Differential-Integral Neural Operator for Long-Term Turbulence Forecasting Hamiltonian Generative Networks

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:20:42.032927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f8b0b7a5-0c65-4fae-b8e0-9577c1e51f90 · inbound

Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations cites this paper.

Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations Hamiltonian Generative Networks

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-16T21:41:17.478382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1db4aa99-585e-4a70-adc7-d26c4349fed3 · inbound

IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video cites this paper.

IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video Hamiltonian Generative Networks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-13T23:47:18.378887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df2100c3-63c3-41f9-9d6b-b6ff264c518f · inbound

Identify Then Project: Contrastive Learning of Latent Dynamics from Partial Observations with Port-Hamiltonian Structure cites this paper.

Identify Then Project: Contrastive Learning of Latent Dynamics from Partial Observations with Port-Hamiltonian Structure Hamiltonian Generative Networks

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-20T19:18:54.490985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a990765f-a198-49b4-aeb1-a35f0ee3028a · inbound

Learning partially observed systems with neural Hamiltonian ordinary differential equations cites this paper.

Learning partially observed systems with neural Hamiltonian ordinary differential equations Hamiltonian Generative Networks

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:10:22.199835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 762bd07a-fd36-47a8-a9f9-2401126f3246 · inbound

When Do Conservation Laws Survive Learned Representations? Certified Horizons for Latent World Models cites this paper.

When Do Conservation Laws Survive Learned Representations? Certified Horizons for Latent World Models Hamiltonian Generative Networks

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T16:29:57.588824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1f179b7e-b72c-4dbf-9cc6-62d01eb2ea2a · inbound

When Do Conservation Laws Survive Learned Representations? Certified Horizons for Latent World Models cites this paper.

When Do Conservation Laws Survive Learned Representations? Certified Horizons for Latent World Models Hamiltonian Generative Networks

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T22:59:01.423666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9c9a15a0-d00a-4aa3-bebc-7de6f51df64b · inbound

PhysRAG: Enhancing Physics-Awareness in Video Generation via Retrieval-Augmented Generation cites this paper.

PhysRAG: Enhancing Physics-Awareness in Video Generation via Retrieval-Augmented Generation Hamiltonian Generative Networks

Reference 58

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T13:19:51.080569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1b4356a3-f7be-4ada-a713-d02ec9ab63ac · inbound

Symplectic Neural Networks for Learning Non-Separable Hamiltonians cites this paper.

Symplectic Neural Networks for Learning Non-Separable Hamiltonians Hamiltonian Generative Networks

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-04T13:09:50.207702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation eb4b549e-bbd4-4d06-a09a-87f20175d48a · 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 Hamiltonian Generative Networks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T06:43:04.655191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d0a41dd-f41a-4748-9660-8bb6d99a2914 · inbound

A matched-integrator evaluation of Hamiltonian neural networks on pendulum and Kepler dynamics cites this paper.

A matched-integrator evaluation of Hamiltonian neural networks on pendulum and Kepler dynamics Hamiltonian Generative Networks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-14T04:16:53.955720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.