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Paper Citation Record · LEDGER

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network

As of 8 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

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

46 of 46 outbound references displayed

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  • verified fuzzy35
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External citation measurements

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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

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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

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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

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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

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source=pdf_text observed=2026-08-06T16:10:25.999162Z digest=sha256:221d93b0ac3b13ab2a1d0a96559f57dc98f8e4c5828b25b21e12c1cc57a36ec0

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

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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

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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

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source=pdf_text observed=2026-08-06T16:10:26.248762Z digest=sha256:22073e8f6dc87c9fdf0dbf5e77c90ed9a37d255d6ee5060b945eb327a3364b75

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

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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

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source=pdf_text observed=2026-08-06T16:10:26.418254Z digest=sha256:d105f47fc965a7ea1b167e4925ad09b4d007d10ec84830e47237cba4ea710ed5

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

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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

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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

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source=pdf_text observed=2026-08-06T16:10:26.645094Z digest=sha256:6e2a4e02ecacd52d6f9ca5e5a5ef38f5ed407a4ad9af414841cba667a7253f71

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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:26.705964Z digest=sha256:a0484e7276e95d06719fae23c7c9eec39bad64d997d3ca6d351af6f6a182e1d6

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

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source=pdf_text observed=2026-08-06T16:10:26.777033Z digest=sha256:d9ba7c7ff63f04b51230ef8bca42169ee077b1ae953346c13c6584866f2daf67

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

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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

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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

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source=pdf_text observed=2026-08-06T16:10:27.015973Z digest=sha256:01f17e06fb8193ad52013357ca3b2235bcfd975001dfdc50a64888072b983250

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

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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

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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

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source=pdf_text observed=2026-08-06T16:10:27.225559Z digest=sha256:a697354dd220e3d737553ed472aa2510c4a80b89f01452731d7339fa3d819122

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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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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

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source=pdf_text observed=2026-08-06T16:10:27.386198Z digest=sha256:f5725ee03f4fe6546cac7b7a695c4f121fd13884f15578ad4d7f8e13dcb733fe

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

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source=pdf_text observed=2026-08-06T16:10:27.493692Z digest=sha256:41d4bd36971e4216bd2b2ebf8301c8ef9b020db27281d1c29b144d55c9f3fa54

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

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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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:27.720527Z digest=sha256:7372610ac459cedb7112ccdbf578a5fbff2ab1aa673b5186b4e36cc96e8ef1b8

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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:10:27.819472Z digest=sha256:ddc14ec44745ede51f1f32957168bbce8ed0618297bb26389b906c84c51aa810

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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:27.971202Z digest=sha256:738191ab66b2dbd437961f7f876d2ab7e97f50ffb42f0628da19142b5c59d4d3

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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:10:28.042532Z digest=sha256:35e421fff6a846747d99b4641aff99801e0e02254cf7dc87724350e879a56fef

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

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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]

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:10:28.201594Z digest=sha256:390ac05d17699888c590d8f7d5c66fed248afbbdf7283790951e96e0d2c42fae

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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:10:28.286524Z digest=sha256:2fd57e037ccebb0a5b2f0be60053a8eb341122de3d37c6969290461a43668dba

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]

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:10:28.372876Z digest=sha256:6e74fc4e4e156ff639a655b4e286dceb5ad91fb248d0176ecfda2b1ff1b30c68

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]

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:10:28.463457Z digest=sha256:96e36278fc6c9b14badc7955bd9861e5a5f7b2b5e3642104ae23e58d275a1521

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

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local_arxiv, observed 2026-08-06T16:10:30.420676Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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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]

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

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source=pdf_text observed=2026-08-06T16:10:28.644859Z digest=sha256:9dada357451a8a5d1390121ed7c468d4688f4d971e0603a29cc9575b4fa691e5

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

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local_arxiv, observed 2026-08-06T16:10:29.970807Z

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source=pdf_text observed=2026-08-06T16:10:28.719779Z digest=sha256:8117904db9e975382ba317fab0f9a52a4608c0013d8cbd0c4033e9945150737a

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

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source=pdf_text observed=2026-08-06T16:10:28.790393Z digest=sha256:5522b2075581c19d8319fe55a6c9f9c5ec5cbca7c133d4059678ae7767a12d7f

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:10:28.858810Z digest=sha256:7d278ddb0598a098ad7f4db9150082c676520c52e2f6a02434c5c7ef272569d2

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]

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

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source=pdf_text observed=2026-08-06T16:10:28.941887Z digest=sha256:23c8f30fbd307e6760e93415030d8283c155ea431a1a89c908b57b5a90df518e

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]

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

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source=pdf_text observed=2026-08-06T16:10:29.049375Z digest=sha256:9c1b4cc5f5ac588bf5c6ba9acb26ba2337e725caae1523de77bc5524e4039694

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

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source=pdf_text observed=2026-08-06T16:10:29.161313Z digest=sha256:196b2a12343142e46076c1926e4a13752b511bb96cdd6193a656064f8cf2abcd

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

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source=pdf_text observed=2026-08-06T16:10:29.242414Z digest=sha256:72e01990a901ddbc24623d20c2d9d0ab985903f5793f9af6735293f6eea48992

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
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raw_fallback, observed 2026-08-06T16:10:32.971721Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T16:10:29.337844Z digest=sha256:b62f0eca773db0203a0e855f5b5c816f4583275d5c9eb0492d96b319360ab16c

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

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source=pdf_text observed=2026-08-06T16:10:29.419051Z digest=sha256:b4b5af90bb91c11ae2287bea39270744750000fc6668071c5630e197cbe5a29e

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

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

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source=pdf_text observed=2026-08-06T16:10:29.498566Z digest=sha256:9d384d9978180645ea715e31338140e5a640e17feba8ec3d4222d69c65fb4708

Pith citing papers

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