Pith. sign in

Paper Citation Record · LEDGER

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network

As of 16 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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:25.773098Z digest=sha256:17c3716a8db75f6bdd821b14324d4c98c859a896c4c5b44e42d2d1ad99ec2e19

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:25.848839Z digest=sha256:b2585530899b580d85e31e42052d69038710ca5ed26e3c98ac8eaf1a3cd62de8

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:25.936232Z digest=sha256:86fd37f2565f09956b2fa939a2ffe5c51741e7ae48839b8667523e956ef98ba6

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:25.999162Z digest=sha256:250aeb3874ee36e6e4ba062bd180429742b6e4651e8e20ce4e67f579aa1e4235

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:26.094424Z digest=sha256:c83a70bd9a35a94132ccf1986b07dd0e35b3e1a33f98c540c0cef4deff08c938

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:26.158916Z digest=sha256:7e4162bd837aecddfb16cbbe7cfd0edb5c40b715eb36eec8e4e83b9f9eb33fc9

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:26.248762Z digest=sha256:6e08aeaadb9a2eef12c6b82e9895bec43a2f69a8e3374519451c20e17f293ffe

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:26.346992Z digest=sha256:a863619a025e101abba6a5d28a1285f1ead07c4a6da19b5f9fc716b192cb98e8

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:26.418254Z digest=sha256:9c0650109affdc86586e86728866a8d127416152a636725b6aa80e674f543d93

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:26.493501Z digest=sha256:527aedb28ac5605d60e592fc5e04a1b5ca9fc96693922920523393bdef80fd84

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:26.559859Z digest=sha256:0b406342042124a9cd43bf5c24456b2c68a5176708c4ef0ffb455a07391a3d5e

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:26.645094Z digest=sha256:1d39d3972de7d582e3207e28149c55c887475616fd9c5d2de784f440d4367b65

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.

source=pdf_text observed=2026-08-06T16:10:26.705964Z digest=sha256:ceeb4953e125f198835cd40889c8754a29a84b93f44cc04453ddbbff303f06c3

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:26.777033Z digest=sha256:bd3996ee58722c256b8b30695639da8ef9fc8fbeaa458caef6ea49a1f814f580

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:26.862262Z digest=sha256:1aa33dfd6606610662eb2d312c996a4bbea7ba9556bb13549ee315d4f967b609

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.

source=pdf_text observed=2026-08-06T16:10:26.961941Z digest=sha256:a581d78d3ae214ee3c192c944a1a876de424440b91017370e703268decc46e87

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.

source=pdf_text observed=2026-08-06T16:10:27.015973Z digest=sha256:9b7de104ce60206ea594f03f84502ebcbeed438ba7b3a249b449049924cd5940

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:27.089739Z digest=sha256:2381537bdc9ae8084c32e61ab3cb9ef63bdc8151a1b10ba459f58fa5b88975e5

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:27.160178Z digest=sha256:f5180999a3e1164f55daf289b8f84b3e62bd7523aa58e398980ab8f44329d48c

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.

source=pdf_text observed=2026-08-06T16:10:27.225559Z digest=sha256:d5476a85f46841debfa4e44f55fb24c8bcc418329065fdf2be95e4acab4a4a8e

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:27.294498Z digest=sha256:a96c0e09186d98467148bb992733cb132e0d32ed152c53b97d9f69c069417629

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:27.386198Z digest=sha256:edbae82c4e9b6ae492a4adff6f4ad7ddc2258bdd08b57bc105980d1fbe7d96ef

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.

source=pdf_text observed=2026-08-06T16:10:27.493692Z digest=sha256:4563d001a684affad052c0cb4dc2918e517192a72c31cad463b1b93d70788a9c

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:27.589181Z digest=sha256:79b6dcdac6c3b39b7664e9957fbadb44110b2a33b3766b329b368b1aa3a9ada4

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.

source=pdf_text observed=2026-08-06T16:10:27.720527Z digest=sha256:b42f131b0dc453508aac09eef92a4e2a9b55457cee82f0ed3e91e4663de88c1c

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:27.819472Z digest=sha256:3d7fc0dc84ac323186d8543134ab96f0cd7be8cded2f5d2859fff55b31408221

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:27.893375Z digest=sha256:2a04396416f9a4d2e45f9f4c0d4be917b57629a9fe00c3844f2520c5c60fb3f7

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.

source=pdf_text observed=2026-08-06T16:10:27.971202Z digest=sha256:60b216ce4e0b7844ab91f1019d2af018e692273066cc7510428517a5345169bc

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:28.042532Z digest=sha256:901cadd8cff93e497a1ac4016395b0fbb77f15d72b53ab765068d8d58f980ca2

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:28.115102Z digest=sha256:3810563add678f41bc0914e480038eb6c0af2c6b2249e95a5cd4729029936a06

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:28.201594Z digest=sha256:1e2609efe231871ec9f2eab7a6333ab0bad92b413919ae88aee47c1c7f75ce46

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:28.286524Z digest=sha256:b499633cd8a692c2c575b7cab53ddfebf20a0357132b1d94be7038fbe20309e9

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:28.372876Z digest=sha256:c28c48c5c63de8f98c5a3070c4808c637bc8697da1f50bb1328220be1ec7d4dc

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:28.463457Z digest=sha256:05b962bc09d723a659d1757fefc0a48c47f4982fb60514081c7c5080653f7133

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:28.547485Z digest=sha256:a2fecca6542aaaf9438b76514fb44be47b649596cefd8ab8d893529481b8d864

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:28.644859Z digest=sha256:6ad01133e2693604c5358ed19eb7168ffb5fb04ce18e76baf943c9eba1004af2

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:28.719779Z digest=sha256:bd729fe1bb3119e884efa7569792d54bf4db0508c1aa43ae11d88a9235c71b36

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:28.790393Z digest=sha256:ea39da2138dba9bc787f13571ecc6a0f260fa107707c5b15ebae7de07196b45b

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.

source=pdf_text observed=2026-08-06T16:10:28.858810Z digest=sha256:a1e730d4fa8cc1be2c3f370faf2f5f2845de59daf42df33ecd44fa62b2a5bd8e

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:28.941887Z digest=sha256:1a265f022940b23db569145ec6c4e776b1a68ed3e3358cbc1f2484df8aed79d6

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:29.049375Z digest=sha256:00fe0d6803be2f5187f3002bf7b83b4ff4f85cc35294565dcc33bf000da839bb

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:29.161313Z digest=sha256:671819b501beedd1176ef191abb7191f76bc6d2e8c4571ff9757a26abf12196e

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:29.242414Z digest=sha256:b70e2b887fc65230b4c134f5d1727ef2ba73f1ef0a88544dc8197277f0d34b40

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:29.337844Z digest=sha256:6f208be2fc30ac49e828427857544c0acfc89395c265b66cbb8d71d130d5a15a

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:29.419051Z digest=sha256:45ab1fc7598933576b3215284f23e947088a33f8c48c679c99bc2812a66136d3

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T16:10:29.498566Z digest=sha256:a9445a2755559af8a6a8f89e261b4abe6699dbc4628ac60fcac1b6915acb5b8d

Pith citing papers

No inbound Pith citation observations are available.