Pith. sign in

Paper Citation Record · LEDGER

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning

As of 7 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2608.03378.

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

pith.paper-citation-record.v1
2608.03378 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:08:42.832965Z

measured 33 of 33 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

33 of 33 outbound references displayed

  • verified exact1
  • verified fuzzy25
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b46c7034-1466-4292-9786-8532b5f2727c · outbound

This paper cites Wind tunnel and hover performance test results for multicopter UAS vehicles,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Wind tunnel and hover performance test results for multicopter UAS vehicles,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:47.796450Z

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.

source=pdf_text observed=2026-08-05T20:08:39.207069Z digest=sha256:3092f212160090f7da5602b0eb8ba5773153a81662b6dd9ad552b619a690d3f5

Observation 3aac7894-019c-48d7-96b8-48dc892c2d28 · outbound

This paper cites Wind tunnel test of an unmanned aerial vehicle (UA V),.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Wind tunnel test of an unmanned aerial vehicle (UA V),

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:47.629393Z

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.

source=pdf_text observed=2026-08-05T20:08:39.289466Z digest=sha256:6ed3b24f642ed0d61afd3112260ff81bbf7c7da6a28e54c3ad8a77a4c1d90080

Observation 792ea295-d808-40f2-ad06-31f36f8c36e8 · outbound

This paper cites Development of a wind tunnel experimental setup for testing multirotor unmanned aerial vehicles in turbulent conditions,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Development of a wind tunnel experimental setup for testing multirotor unmanned aerial vehicles in turbulent conditions,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:47.407307Z

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.

source=pdf_text observed=2026-08-05T20:08:39.426022Z digest=sha256:34fbb5547b50b9fb9f0365f5887c54fce7a600eab5888af7d177b9c90c2c1704

Observation 469b81b2-cb10-45ea-911d-72c8123edaf3 · outbound

This paper cites Commercial wind-tunnels for UA Vs testing,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Commercial wind-tunnels for UA Vs testing,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:47.221624Z

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.

source=pdf_text observed=2026-08-05T20:08:39.597168Z digest=sha256:562c800bb6c14bd14d800c4ef6947bcc843d10d77ef9399f0876ef5806fd9dbb

Observation 86c283bc-bff6-4394-a307-11e64d576a58 · outbound

This paper cites Science, technology and the future of small autonomous drones,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Science, technology and the future of small autonomous drones,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-05T20:08:39.697585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:08:39.697585Z digest=sha256:a638ba91ebeaee3d1689369c14b1cc583b54360811c250838b209e4e4058fcc8

Observation ffa32df3-803c-49a7-b309-4fa304650fbc · outbound

This paper cites Lift production in the hovering hummingbird,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Lift production in the hovering hummingbird,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:47.056618Z

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.

source=pdf_text observed=2026-08-05T20:08:39.949043Z digest=sha256:35b436622406762c9f1a9b927273c16c228f21aa93f0ce65b2ec4975500ea257

Observation 8df11c49-5d19-4b42-8f07-56899c4dd3e3 · outbound

This paper cites Acoustic and aerodynamic design and characterization of a small-scale aeroacoustic wind tunnel,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Acoustic and aerodynamic design and characterization of a small-scale aeroacoustic wind tunnel,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:46.867751Z

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.

source=pdf_text observed=2026-08-05T20:08:40.070134Z digest=sha256:1fc007b908d17c9a907277190bd34d95d7b59408ddacaab896e35183dafc1274

Observation 77276c93-d2c8-431d-8c3a-c3f26b12e4e5 · outbound

This paper cites Design and performance of a small-scale aeroacoustic wind tunnel,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Design and performance of a small-scale aeroacoustic wind tunnel,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:46.706620Z

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.

source=pdf_text observed=2026-08-05T20:08:40.206798Z digest=sha256:c1e66540be56eae4f2492d1b5853030d9d7923a437e8e3aa48d8f6ce2c0c89b8

Observation efe28585-8acc-41ca-aad4-126a6fa0d5a7 · outbound

This paper cites Atmospheric boundary layer sim- ulation in a new open-jet facility at LSU: CFD and experimental investigations,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Atmospheric boundary layer sim- ulation in a new open-jet facility at LSU: CFD and experimental investigations,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:46.512847Z

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.

source=pdf_text observed=2026-08-05T20:08:40.354098Z digest=sha256:403eeb6b0d6a5532835b6501582722e6dcf683986502ec42d5043e9593229545

Observation 258f9da5-030b-496b-8a1c-c698f2c9a051 · outbound

This paper cites Realization of a large-scale turbulence field in a small wind tunnel,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Realization of a large-scale turbulence field in a small wind tunnel,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:46.297787Z

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.

source=pdf_text observed=2026-08-05T20:08:40.497793Z digest=sha256:f46a05db0147cb28908d38f0d2da01044628ab92597e9f08876105338ea82508

Observation da5c009a-6f15-47a4-b86a-b5ae3eea22d4 · outbound

This paper cites Atmospheric turbulence simulation tech- niques with application to flight analysis,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Atmospheric turbulence simulation tech- niques with application to flight analysis,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:46.170583Z

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.

source=pdf_text observed=2026-08-05T20:08:40.665115Z digest=sha256:bbf6d6e14f027e76b4eb7d7009827f361e62d9c0b4b862777c65e9378ebeb344

Observation d60495ab-cf1d-4376-ad3f-a16f31f5a74c · outbound

This paper cites an unresolved cited work.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-05T20:08:46.011525Z

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.

source=pdf_text observed=2026-08-05T20:08:40.800615Z digest=sha256:1852eaf85af0bb7d46e7a2d9b8e403823421567ba7699cbe43fdf719b6479f94

Observation 93cad9c9-2d6f-4695-a2f7-9ffc86041372 · outbound

This paper cites an unresolved cited work.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-05T20:08:45.837171Z

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.

source=pdf_text observed=2026-08-05T20:08:40.941836Z digest=sha256:0c3adabf5a22aaedb24e1979e0f609b058e13021203a9cb3b8abb9d32c201857

Observation e6ccad98-3333-4823-a5c8-bd155bf2d770 · outbound

This paper cites Propeller-wing interaction using rapid computational methods,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Propeller-wing interaction using rapid computational methods,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:45.652734Z

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.

source=pdf_text observed=2026-08-05T20:08:41.097995Z digest=sha256:732b292263395ad5fab10ed8628ae560b6db2671c217cd53a470f16d7adb6394

Observation ab6b4949-512e-4903-8378-648b407fdbb3 · outbound

This paper cites Computational study of propeller–wing aerodynamic interaction,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Computational study of propeller–wing aerodynamic interaction,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:45.433829Z

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.

source=pdf_text observed=2026-08-05T20:08:41.239468Z digest=sha256:bd32b556b08431a46377568cf5e6dea4f27941434f8c6090ee2bebd77e788e92

Observation d4e1fd86-41b4-4423-b940-9b507f3fccae · outbound

This paper cites Evaluating the longitudinal stability of an UA V using a CFD-6dof model,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Evaluating the longitudinal stability of an UA V using a CFD-6dof model,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:45.237565Z

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.

source=pdf_text observed=2026-08-05T20:08:41.317898Z digest=sha256:f9d10ac19bfe9efd33e39c72d6faadbaba03a5674b5c8c3f46e2b734db4191ca

Observation 2e081a04-0ed2-4477-9a14-bcc5d844682c · outbound

This paper cites Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-05T20:08:41.381480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:08:41.381480Z digest=sha256:6a2e5888bc4a6e7fd9b78a3ec09d43801d4bedb2b6e7b1a6cf25f0f34fbfd5b4

Observation ca7028c7-c5b8-4615-9b64-552c6a81087a · outbound

This paper cites Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-05T20:08:41.448922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:08:41.448922Z digest=sha256:d4e284ca91c0e002d628201fbe5993b9a2d8067f273225c1b9d15df09de925b1

Observation 36497bd9-13e9-4220-ac66-db763f5e2c92 · outbound

This paper cites Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-05T20:08:41.553336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:08:41.553336Z digest=sha256:d0058e4d8cf35fd5ad2b0cbc5f8534fcb9e1f74eeb689c9f8e13fa59ed23f6e7

Observation fab63f52-1c19-4e66-9626-b5921528b3b9 · outbound

This paper cites Physics- informed neural networks (PINNs) for fluid mechanics: A review,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Physics- informed neural networks (PINNs) for fluid mechanics: A review,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:45.094463Z

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.

source=pdf_text observed=2026-08-05T20:08:41.615076Z digest=sha256:2b362172ef5f032295b2381799455a19dde7efcc21edb7004c5515c41d5cfd37

Observation 67c6d189-c344-41a1-8d14-5f7a6ed97464 · outbound

This paper cites Deep learning of vortex-induced vibrations,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Deep learning of vortex-induced vibrations,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:45.021434Z

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.

source=pdf_text observed=2026-08-05T20:08:41.724280Z digest=sha256:2f82a7aa6b2b40b7dcf23c192c24bc9d59a24b3205cfa461a5f328344f291bd7

Observation 4eba3435-3cae-429c-be2c-146388fc8e9d · outbound

This paper cites Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T20:08:41.817361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:08:41.817361Z digest=sha256:0abd79267217404944bd30eec2671625b64ea2b3fd58bec3ab20313f14f42339

Observation 41df5ad4-c4bf-4449-9a45-2d9433987404 · outbound

This paper cites State–space modeling for control based on physics-informed neural networks,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning State–space modeling for control based on physics-informed neural networks,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:44.955747Z

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.

source=pdf_text observed=2026-08-05T20:08:41.894060Z digest=sha256:042d50e9a96f1ecd6b2322c6212fbdaa72f760efb490a03822ba0d69a30efcb9

Observation 0da14c61-a4c6-499b-b7c7-0a8204f2fd61 · outbound

This paper cites Pressing and rubbing: physics-informed features facilitate haptic terrain classi- fication for legged robots,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Pressing and rubbing: physics-informed features facilitate haptic terrain classi- fication for legged robots,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:44.921805Z

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.

source=pdf_text observed=2026-08-05T20:08:41.982222Z digest=sha256:2cf2e5b8ba5e5b0a25f13e4d2dc33cf717763d43095d182afca27a697593e5b8

Observation f7d70ecc-7ed9-4657-b9a0-fa63aae5167f · outbound

This paper cites Stochastic online op- timization for cyber-physical and robotic systems,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Stochastic online op- timization for cyber-physical and robotic systems,

Reference 25

Resolution
verified exact
raw_fallback, observed 2026-08-05T20:08:43.184697Z

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.

source=pdf_text observed=2026-08-05T20:08:42.058457Z digest=sha256:fd216ba005142d39fb259a5b486d42e81a52957b2f375fa7cc1b916e2309070a

Observation 58cb0a11-a7f0-4181-8c79-e5acc17e67e8 · outbound

This paper cites A simple learning strategy for high-speed quadrocopter multi-flips,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning A simple learning strategy for high-speed quadrocopter multi-flips,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:44.770828Z

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.

source=pdf_text observed=2026-08-05T20:08:42.161074Z digest=sha256:26014d9ca7471df489f5ef5eefc3defd3b8800d785be7b97a50c88d7511f36d6

Observation 7ebb76fd-ba74-4db1-be48-e86f50d7f09a · outbound

This paper cites Nonholonomic yaw control of an underactuated flying robot with model-based reinforcement learning,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Nonholonomic yaw control of an underactuated flying robot with model-based reinforcement learning,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:44.607696Z

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.

source=pdf_text observed=2026-08-05T20:08:42.230874Z digest=sha256:49f9b9fe6137646ecf9ff89917968f595c7fff08f040aa047188d83c447d4948

Observation 098ec277-c321-40ba-9de1-163b02fca1fc · outbound

This paper cites A learning- based iterative control framework for controlling a robot arm with pneumatic artificial muscles,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning A learning- based iterative control framework for controlling a robot arm with pneumatic artificial muscles,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:44.415780Z

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.

source=pdf_text observed=2026-08-05T20:08:42.322919Z digest=sha256:2ab3c88b0f5068cb9be911dbeaded65cf9d01032527272051b9b1d0b59da7705

Observation cabd70c3-4a63-4283-ab05-449d8a4fe8e0 · outbound

This paper cites Data-efficient online learning of ball placement in robot table tennis,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Data-efficient online learning of ball placement in robot table tennis,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:44.257283Z

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.

source=pdf_text observed=2026-08-05T20:08:42.409763Z digest=sha256:a0ceeeea0cc8126b4e77c19a3449a0bdb6069b3da14b5e9992b0799112870e3a

Observation da3539fd-cb6e-4936-b9e9-2ee6d3e815fe · outbound

This paper cites A fast and reliable pick-and- place application with a spherical soft robotic arm,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning A fast and reliable pick-and- place application with a spherical soft robotic arm,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:44.028970Z

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.

source=pdf_text observed=2026-08-05T20:08:42.538098Z digest=sha256:8ec0fc9b80ee3379edddf168f89a95a4bdfeb011113424e972f7688865ccb396

Observation bb2f74fe-8b5f-414f-966f-3eedc6c93a6a · outbound

This paper cites Learning-based parametrized model predictive control for trajectory tracking,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Learning-based parametrized model predictive control for trajectory tracking,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:43.799132Z

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.

source=pdf_text observed=2026-08-05T20:08:42.607677Z digest=sha256:74797e55b0d51cc2dfabdda7cdea3801d05b88fdcf68d4d46252a15770704054

Observation d3990eff-820f-4c85-92d2-497e8c7adb5d · outbound

This paper cites Embodied intelligence for sustainable flight: A soaring robot with active morphological control,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Embodied intelligence for sustainable flight: A soaring robot with active morphological control,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:43.590552Z

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.

source=pdf_text observed=2026-08-05T20:08:42.733883Z digest=sha256:5e5a8a416fcf0d568eef62618f47fee63ba379d5c31f82729686c86d07934212

Observation 909d251c-04a4-45a6-9a9f-d9a4045ca008 · outbound

This paper cites Gaussian processes for regression,.

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning Gaussian processes for regression,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:43.410793Z

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.

source=pdf_text observed=2026-08-05T20:08:42.832965Z digest=sha256:ae839606ed5203b2f5be0aa261289c357aebc4fff679ed98ad4ce3352b1ec7d9

Pith citing papers

No inbound Pith citation observations are available.