Paper Citation Record · LEDGER

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network

As of 7 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2507.14467.

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

pith.paper-citation-record.v1
2507.14467 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:10:29.498566Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

46 of 46 outbound references displayed

verified exact3
verified fuzzy35
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 681600a7-3b98-4242-9285-aec5a9c99097 · outbound

This paper cites Symplectic geometric algorithms for Hamiltonian systems[M].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Symplectic geometric algorithms for Hamiltonian systems[M]

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:40.197312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c5e26f95-7e56-40f2-93d7-47d82d0ee5b8 · outbound

This paper cites Structure-Preserving Algorithms for Ordinary Differential Equations[M].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Structure-Preserving Algorithms for Ordinary Differential Equations[M]

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:39.904770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c5f9c466-778d-47bc-a14a-2bc86e8047a3 · outbound

This paper cites M´ ecanique al´ eatoire.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network M´ ecanique al´ eatoire

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:39.629513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 37cf5456-1111-49b8-86b1-da6c35edf058 · outbound

This paper cites Conserved quantities and symmetries related to stochastic dynamical systems[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Conserved quantities and symmetries related to stochastic dynamical systems[J]

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:39.378566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7ba1bdf8-82f3-4898-b4af-51a44f9f9926 · outbound

This paper cites Mean-square symplectic methods for Hamiltonian systems with multiplicative noise.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Mean-square symplectic methods for Hamiltonian systems with multiplicative noise

Reference 5

Resolution: verified exact; doi, observed 2026-08-06T16:10:29.679810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8f8d1f01-2dad-4833-a391-bfa3991e334e · outbound

This paper cites Symplectic methods for Hamiltonian systems with additive noise[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Symplectic methods for Hamiltonian systems with additive noise[J]

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:39.073930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c36efc21-eec9-4cad-9b6b-26ed4ea29929 · outbound

This paper cites Predictor–corrector methods for a linear stochastic oscillator with additive noise[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Predictor–corrector methods for a linear stochastic oscillator with additive noise[J]

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:38.754570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 071e9e9e-fbec-4d46-9442-a6838cad2425 · outbound

This paper cites Variational integrators and generating functions for stochastic Hamiltonian sys- tems[D].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Variational integrators and generating functions for stochastic Hamiltonian sys- tems[D]

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:38.444958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d1a7c3aa-6aee-406f-b5bf-5938be85308c · outbound

This paper cites Stochastic variational integrators[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Stochastic variational integrators[J]

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:38.235394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ee18461d-f73c-453f-8e1d-007aee5015f7 · outbound

This paper cites High-order symplectic schemes for stochastic Hamiltonian systems[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network High-order symplectic schemes for stochastic Hamiltonian systems[J]

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:38.061493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3f3eaf89-3d69-4611-87b6-18406be66807 · outbound

This paper cites Symplectic integration of stochastic Hamiltonian systems[M].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Symplectic integration of stochastic Hamiltonian systems[M]

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:37.865090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1628ced6-a77e-4969-9b24-506700d1f2df · outbound

This paper cites Neural ordinary differential equations[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Neural ordinary differential equations[J]

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:37.682139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5fd6068d-2cff-4467-acdb-6665a628345f · outbound

This paper cites Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T16:10:26.705964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd3362ea-3556-40b2-a605-2851b3715c1b · outbound

This paper cites Pde-net: Learning pdes from data[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Pde-net: Learning pdes from data[J]

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:37.560498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7a8452de-9b15-41c4-86bd-51c1d69ad649 · outbound

This paper cites PDE-Net 2.0: Learning PDEs from data with a numeric-symbolic hybrid deep network[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network PDE-Net 2.0: Learning PDEs from data with a numeric-symbolic hybrid deep network[J]

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:37.365522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 541f25d3-dc9d-4deb-a685-64633c49cd5f · outbound

This paper cites SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T16:10:26.961941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d3e0ae1-aaec-4edc-845f-38498b806ab9 · outbound

This paper cites Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T16:10:27.015973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a0bca8c-47e3-4c13-9dfe-ba3556bcdeff · outbound

This paper cites Hamiltonian neural networks[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Hamiltonian neural networks[J]

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:37.069325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d5115624-cd16-4ea5-a6c0-e7db9643399c · outbound

This paper cites Symplectic recurrent neural networks[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Symplectic recurrent neural networks[J]

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:36.870361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ff4b083b-91ce-4eee-923f-722793d1698a · outbound

This paper cites Deep Hamiltonian networks based on symplectic integrators.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Deep Hamiltonian networks based on symplectic integrators

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T16:10:27.225559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 868a6873-71a0-4c4a-aafa-b73a0c3b335e · outbound

This paper cites SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems[J]

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:36.707271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 390ee151-b340-4e38-9908-6caa01b757ae · outbound

This paper cites Journal of Computational Physics, 2021, 437(4):110325.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Journal of Computational Physics, 2021, 437(4):110325

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:36.516689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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

This paper cites Hamiltonian Generative Networks.

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 219bd012-301e-49a1-9f53-8d00bfb5c7c4 · outbound

This paper cites Data-driven prediction of general Hamiltonian dynamics via learning exactly- symplectic maps[C].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Data-driven prediction of general Hamiltonian dynamics via learning exactly- symplectic maps[C]

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:36.332799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2bb294b5-de86-46e4-8560-0e791f86b4df · outbound

This paper cites Nonseparable Symplectic Neural Networks.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Nonseparable Symplectic Neural Networks

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T16:10:27.720527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58805026-bdf8-40d6-945f-abaabe7fe418 · outbound

This paper cites Structure-preserving method for reconstructing unknown Hamiltonian systems from trajectory data[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Structure-preserving method for reconstructing unknown Hamiltonian systems from trajectory data[J]

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:36.120119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a7972a0e-c387-46be-9394-468dc3ef1275 · outbound

This paper cites Learning Hamiltonian systems considering system symmetries in neural networks[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Learning Hamiltonian systems considering system symmetries in neural networks[J]

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:35.872041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e80866d9-d980-4b35-9142-301e691cc3da · outbound

This paper cites an unresolved cited work.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T16:10:27.971202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 425647d5-1cbf-4e19-98d9-c15867173321 · outbound

This paper cites Detecting stochastic governing laws with observation on stationary distributions[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Detecting stochastic governing laws with observation on stationary distributions[J]

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:35.679889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9c74bad1-a32e-44cd-b7b7-3d3db31d7b15 · outbound

This paper cites Scalable inference in sdes by direct matching of the fokker–planck–kolmogorov equation[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Scalable inference in sdes by direct matching of the fokker–planck–kolmogorov equation[J]

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:35.493056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 25319dcf-534d-419c-bcbc-9ec7d3b9d09e · outbound

This paper cites Variational inference for stochastic differential equations[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Variational inference for stochastic differential equations[J]

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:35.314455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation aea767dc-eaac-42ad-9f34-845f997fe562 · outbound

This paper cites Black-box variational inference for stochastic differential equations[C].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Black-box variational inference for stochastic differential equations[C]

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:35.128620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4b9b7f3d-f4c5-41de-b15e-64c4a7fddae5 · outbound

This paper cites Modeling continuous stochastic processes with dynamic normalizing flows[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Modeling continuous stochastic processes with dynamic normalizing flows[J]

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:34.971573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bca992d0-13c6-46dc-a4b8-52aa768dafaf · outbound

This paper cites Normalizing field flows: Solving forward and inverse stochastic dif- ferential equations using physics-informed flow models[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Normalizing field flows: Solving forward and inverse stochastic dif- ferential equations using physics-informed flow models[J]

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:34.760948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bac61732-4f65-4b8d-a017-4c437485537d · outbound

This paper cites Data-driven Effective Modeling of Multiscale Stochastic Dynamical Systems.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Data-driven Effective Modeling of Multiscale Stochastic Dynamical Systems

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:10:30.420676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 224e2b4f-3a9d-4445-b096-e7d98673faab · outbound

This paper cites Learning stochastic dynamical system via flow map operator[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Learning stochastic dynamical system via flow map operator[J]

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:34.246114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fa9e7cdb-9569-45e1-977c-7c2ab68f1902 · outbound

This paper cites Modeling Unknown Stochastic Dynamical System Subject to External Excitation.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Modeling Unknown Stochastic Dynamical System Subject to External Excitation

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:10:29.970807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 957766a6-8595-4bbf-ae20-1869b619ae8b · outbound

This paper cites Modeling unknown stochastic dynamical system via autoen- coder[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Modeling unknown stochastic dynamical system via autoen- coder[J]

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:34.042974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6043a60e-6649-4047-b5f9-d60ada7ba83d · outbound

This paper cites A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical Systems.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical Systems

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T16:10:28.858810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 704394d3-ac62-4f89-8bcf-3f2f4c49a253 · outbound

This paper cites Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation[J]

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:33.858061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d458d93d-bbeb-4027-b546-3fecc45bb602 · outbound

This paper cites Learning a class of stochastic differential equations via numerics- informed Bayesian denoising[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Learning a class of stochastic differential equations via numerics- informed Bayesian denoising[J]

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:33.653407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b4f6bdb7-2f96-4f65-bced-aecbad9e6392 · outbound

This paper cites Learning Parameters of a Class of Stochastic Lotka-Volterra Systems with Neural Networks[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Learning Parameters of a Class of Stochastic Lotka-Volterra Systems with Neural Networks[J]

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:33.419076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9b5fb1f7-6fec-4f27-b8ce-e251039da2e8 · outbound

This paper cites Quadrature Based Neural Network Learning of Stochastic Hamil- tonian Systems[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Quadrature Based Neural Network Learning of Stochastic Hamil- tonian Systems[J]

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:33.228854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f79d380a-2a9b-4964-80c6-534e94aaa354 · outbound

This paper cites Journal of Computational Physics, 2023, 494: 112495.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Journal of Computational Physics, 2023, 494: 112495

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:32.971721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2074b613-e120-490b-8b23-a6321a7cd4b2 · outbound

This paper cites Numerical methods for stochastic systems preserv- ing symplectic structure[J].

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Numerical methods for stochastic systems preserv- ing symplectic structure[J]

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:31.399822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a844b01a-389f-4cec-ac9e-94ff0052fe29 · outbound

This paper cites Numerical simulation of a linear stochastic oscillator with additive noise, Appl.Numer.Math.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Numerical simulation of a linear stochastic oscillator with additive noise, Appl.Numer.Math

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:30.884134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.