Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T16:15:39.470002Z
Paper Citation Record · LEDGER
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling
As of 22 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2501.13415.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
21 of 21 outbound references displayed
- verified exact0
- verified fuzzy20
- unresolved1
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 3a314a5d-4b46-48bd-a6ad-ccbc05c80766 · outbound
This paper cites Assessment of inner–outer interactions in the urban boundary layer using a predictive model.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Assessment of inner–outer interactions in the urban boundary layer using a predictive model
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:40.002276Z
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 14c67ae2-ed0b-465c-9095-b19e28de26e2 · outbound
This paper cites Data-driven assessment of arch vortices in simplified urban flows.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Data-driven assessment of arch vortices in simplified urban flows
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.972859Z
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 843ea6d1-02a9-4e3e-830b-4b09e6999487 · outbound
This paper cites The transformative potential of machine learning for experiments in fluid mechanics.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling The transformative potential of machine learning for experiments in fluid mechanics
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.958866Z
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 63d5d262-33f9-4f14-b37d-65d0c3dc9d4d · outbound
This paper cites Pedestrian exposure to black carbon and pm2.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Pedestrian exposure to black carbon and pm2
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.939196Z
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 19a810ed-36df-489d-850e-cb5f3f5c52b9 · outbound
This paper cites Study of interscale interactions for turbulence over the obstacle arrays from a machine learning perspective.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Study of interscale interactions for turbulence over the obstacle arrays from a machine learning perspective
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.920699Z
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 467b67fe-1bf4-4f11-8928-db40d27480ac · outbound
This paper cites Using machine learning to predict urban canopy flows for land surface modeling.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Using machine learning to predict urban canopy flows for land surface modeling
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.886214Z
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 c2d04fb0-4778-4925-aa2c-c12f1ac3c909 · outbound
This paper cites A reduced order model for turbulent flows in the urban environment using machine learning.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling A reduced order model for turbulent flows in the urban environment using machine learning
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.855860Z
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 1b6cd34e-fe74-423e-aedb-552cbd091f22 · outbound
This paper cites Machine learning accelerated turbulence modeling of transient flashing jets.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Machine learning accelerated turbulence modeling of transient flashing jets
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.835539Z
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 11c87e02-a0b7-4355-8759-34e4653f99dd · outbound
This paper cites A novel spatial-temporal prediction method for unsteady wake flows based on hybrid deep neural network.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling A novel spatial-temporal prediction method for unsteady wake flows based on hybrid deep neural network
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.814620Z
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 2d5385bf-e4a6-4eb8-8704-641d65750329 · outbound
This paper cites Convolutional neural network and long short-term memory based reduced order surrogate for minimal turbulent channel flow.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Convolutional neural network and long short-term memory based reduced order surrogate for minimal turbulent channel flow
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.787836Z
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 84ab712c-f95a-4e98-a02d-2285ea07964d · outbound
This paper cites Predictive models for flame evolution using machine learning: apriori assessment in turbulent flames without and with mean shear.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Predictive models for flame evolution using machine learning: apriori assessment in turbulent flames without and with mean shear
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.763385Z
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 9eccf2a0-dd0d-4753-8337-10d29b1b910e · outbound
This paper cites Identifying regions of importance in wall- bounded turbulence through explainable deep learning.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Identifying regions of importance in wall- bounded turbulence through explainable deep learning
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:15:39.406394Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 41d9e7f3-d19b-41d9-a1e0-eae36086d351 · outbound
This paper cites The spanwise variation of roof-level turbulence in a street-canyon flow.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling The spanwise variation of roof-level turbulence in a street-canyon flow
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.727945Z
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 c6d8e2e2-8d27-4e6d-bf0c-0b4206eb6410 · outbound
This paper cites Roof-level large-and small-scale coherent structures in a street canyon flow.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Roof-level large-and small-scale coherent structures in a street canyon flow
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.688157Z
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 44099e45-3123-4cb4-93e4-03a9eea1ea39 · outbound
This paper cites The flow around a surface-mounted cube in uniform and turbulent streams.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling The flow around a surface-mounted cube in uniform and turbulent streams
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.666320Z
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 d75b57bc-02c3-474f-9f5e-da028290f908 · outbound
This paper cites Adam: Method for stochastic optimization.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Adam: Method for stochastic optimization
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.648702Z
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 ea94da8c-2355-41d0-85c6-d2d973eb1fe4 · outbound
This paper cites Rectified linear units improve restricted boltzmann machines.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Rectified linear units improve restricted boltzmann machines
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.629439Z
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 3a8c0c2a-47b5-4884-ac94-de6ad3386d2b · outbound
This paper cites Tensorflow: a system for large-scale machine learning.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Tensorflow: a system for large-scale machine learning
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.610060Z
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 4cfbacd6-a56d-44dd-bc70-209e2bf7a888 · outbound
This paper cites Street design and urban canopy layer climate.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Street design and urban canopy layer climate
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.582802Z
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 00247ea1-1773-47fd-965d-62c3897c0fe8 · outbound
This paper cites Quadrant analysis in turbulence research: history and evolution.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Quadrant analysis in turbulence research: history and evolution
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.562034Z
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 560e0111-f7c7-4fc6-8317-0c95513ed01d · outbound
This paper cites Turbulence and the dynamics of coherent structures.
Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling Turbulence and the dynamics of coherent structures
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:15:39.534748Z
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.
Pith citing papers
No inbound Pith citation observations are available.