Pith. sign in

Paper Citation Record · LEDGER

Combining Machine Learning with Recurrence Analysis for resonance detection

As of 12 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2412.19683.

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

pith.paper-citation-record.v1
2412.19683 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:06:48.844673Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:06:48.633994Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T00:06:49.310326Z

Reference resolution

41 of 41 outbound references displayed

  • verified exact3
  • verified fuzzy19
  • unresolved18
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 23516bc7-04ea-42f2-bce1-b8a14feef7db · outbound

This paper cites With d degrees of freedom, it consists of • generalized coordinates qi, i= 1,.

Combining Machine Learning with Recurrence Analysis for resonance detection With d degrees of freedom, it consists of • generalized coordinates qi, i= 1,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.743527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.640512Z digest=sha256:e1ba3d5a8d92dd0faf303d7bb489b0f6693238768e45289b9711dc3e23289519

Observation a77a7786-3268-49cf-960c-421cc13c2f94 · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:06:49.728052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.645847Z digest=sha256:3b084552ccbd520572a0e5dc913a50381a150366b216cb3039136f26b0c97555

Observation 6c287c97-b495-464e-96fa-e07c79c0714c · outbound

This paper cites The initial conditions are taken along the pr = 0 line on the Poincar´ e section in r ∈ [6.36M, 6.43M ] spaced at 0.001M.

Combining Machine Learning with Recurrence Analysis for resonance detection The initial conditions are taken along the pr = 0 line on the Poincar´ e section in r ∈ [6.36M, 6.43M ] spaced at 0.001M

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.679156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.663002Z digest=sha256:fc465a304a47015d1694147ac5d6bf52882e3a04d049048a1a9f75dbb02ef339

Observation 680daf1b-bc03-4aa6-844d-3a84812545b7 · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:06:49.711445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.652487Z digest=sha256:5a914763f53a34457e12e26fd18a6abd37e842be737f3498284f2c72959e7a31

Observation 220d4147-d0bd-4691-b607-4c7b8b9de37e · outbound

This paper cites Knowledge of their locations will allow us to properly model the qual- itatively distinct behavior of the passage through these resonances.

Combining Machine Learning with Recurrence Analysis for resonance detection Knowledge of their locations will allow us to properly model the qual- itatively distinct behavior of the passage through these resonances

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.695345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.657453Z digest=sha256:c7d4728c7ee224164b90d7d5c98a8a511116d29f072935259b7e9ca6c394455d

Observation 0998d4da-60a7-463b-8fa9-fbf11a7102b6 · outbound

This paper cites Lukes-Gerakopoulos and V.

Combining Machine Learning with Recurrence Analysis for resonance detection Lukes-Gerakopoulos and V

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.572869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.716450Z digest=sha256:c25c72ff2c6d0d04ca89f65cec278e4f1d2951c373adc588e7c8d98449fdca82

Observation d4f33661-94c4-4e4c-8776-5546535e12b4 · outbound

This paper cites However, already in a system with 3 degrees of freedom, the Poincar´ e section becomes 4-dimensional and these simple methods are no longer applicable.

Combining Machine Learning with Recurrence Analysis for resonance detection However, already in a system with 3 degrees of freedom, the Poincar´ e section becomes 4-dimensional and these simple methods are no longer applicable

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.663999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.668054Z digest=sha256:0724838bd88ed143fae40f4b2363fb3561cd08a384234b15fec8faf212b8e8de

Observation b12b2139-a049-410a-9745-cbb0828e788f · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:06:49.649353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.673847Z digest=sha256:c4e979246e2e1cf3d6bd8c4006ce7adeec7b7846c4a37b72e795565c6475a795

Observation d0efcb1f-3d96-4d11-ae96-38ca0f59e6b0 · outbound

This paper cites Combining Machine Learning with Recurrence Analysis for resonance detection.

Combining Machine Learning with Recurrence Analysis for resonance detection Combining Machine Learning with Recurrence Analysis for resonance detection

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-11T00:06:49.315940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.633994Z digest=sha256:d80a199d7c4ebe23c43b7efb6ae7ac4bae3aa21fa20369329d90cead282993e4

Observation d795aa53-218a-429d-9d18-d9204ef2591d · outbound

This paper cites 8 shows the result of the basic network applied to the Poincar´ e section of a test particle following a geodesic in the Johannsen-Psaltis spacetime metric (see Sec.

Combining Machine Learning with Recurrence Analysis for resonance detection 8 shows the result of the basic network applied to the Poincar´ e section of a test particle following a geodesic in the Johannsen-Psaltis spacetime metric (see Sec

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.634188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.678801Z digest=sha256:97fe1d6f92aa6b775b1ddca5b94b88d5dfda837716688e0f1e1a1171d08ccc18

Observation ad2fd049-1119-4699-92ef-65a0b995ffe1 · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:06:49.618538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.683923Z digest=sha256:449e54f50b737f0cbbda3a9e1b0b88d88597617a6d6d2bb4498a1109d779aac7

Observation d39a44cd-57ec-4ad7-bf89-6dd3dab1134b · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:06:49.603977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.689116Z digest=sha256:d4089095eecfacb85efb6b657082620f3da8ae760f09a3e17321cffd2091a1a1

Observation decf37f2-6388-40cb-be96-2de7bf7322c2 · outbound

This paper cites Resonance crossing of a charged body in a magnetized Kerr background: an analogue of extreme mass ratio inspiral.

Combining Machine Learning with Recurrence Analysis for resonance detection Resonance crossing of a charged body in a magnetized Kerr background: an analogue of extreme mass ratio inspiral

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T00:06:48.694622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:06:48.694622Z digest=sha256:cfdbc2e9eaf65bbcf172279d5af5ec4f6a8b4347f3706c6f85eb4b2646f1698e

Observation 6f4e2f6e-ede2-41c9-bf87-42f1dfab5c9d · outbound

This paper cites Zelenka, G.

Combining Machine Learning with Recurrence Analysis for resonance detection Zelenka, G

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.587445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.700451Z digest=sha256:613fb4073c22362ff4920e89236ecfe1dce494972648273b9b81fc748f023e1f

Observation 809cee2f-7aaf-4f26-915a-d156fda642c6 · outbound

This paper cites Relativistic Dynamics and Extreme Mass Ratio Inspirals.

Combining Machine Learning with Recurrence Analysis for resonance detection Relativistic Dynamics and Extreme Mass Ratio Inspirals

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T00:06:48.706071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:06:48.706071Z digest=sha256:341dc8a06adfb4fcbb6d9d9c1d5b41ef61e4d0a2933dca61295b7718635299af

Observation cfd7729f-694f-441d-ae04-73a8e7858e10 · outbound

This paper cites Astrophysics with the Laser Interferometer Space Antenna.

Combining Machine Learning with Recurrence Analysis for resonance detection Astrophysics with the Laser Interferometer Space Antenna

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T00:06:48.711313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:06:48.711313Z digest=sha256:9a900c0acf449e557fd2ed77f10e06db09f232cdfdf63ea3998461e5e25a4b7a

Observation 86bc5ecb-00cc-4be9-aebc-839537de981b · outbound

This paper cites Free motion around black holes with discs or rings: between integrability and chaos - III.

Combining Machine Learning with Recurrence Analysis for resonance detection Free motion around black holes with discs or rings: between integrability and chaos - III

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-11T00:06:48.721516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:06:48.721516Z digest=sha256:fe942d0b39f1e63a2c9e631d3ebdba54ebcaef0160689bff8ba81e41022c7316

Observation 6b567a60-4016-4c7d-8748-1a1d87087bec · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-11T00:06:48.726536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:06:48.726536Z digest=sha256:22c8c9c1c28e81878681d10a3f4af0e4ac7491916ecc7529e275aa8569ce6206

Observation 8e7484ec-faf2-4e01-a0f6-8605ba0eb179 · outbound

This paper cites Marwan, M.

Combining Machine Learning with Recurrence Analysis for resonance detection Marwan, M

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.558483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.730854Z digest=sha256:eddd4061c956974e89b1bdca68ce3ad5d6d2a13e0373959bb536b2e1ec9d28eb

Observation b47427bb-4db9-4724-8ee3-b8af0225cf83 · outbound

This paper cites A Metric for Rapidly Spinning Black Holes Suitable for Strong-Field Tests of the No-Hair Theorem.

Combining Machine Learning with Recurrence Analysis for resonance detection A Metric for Rapidly Spinning Black Holes Suitable for Strong-Field Tests of the No-Hair Theorem

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-11T00:06:48.735513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:06:48.735513Z digest=sha256:71704eacd91f48dd5f8ce2832ed7eb8073df7f33de5f8110090f3856e72c960b

Observation a8241158-7f91-4d3d-a6de-fbb42129513d · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 21

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:06:49.543511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.739936Z digest=sha256:66f448c49e6a12b6c0b1baf5c8eafa955f27379f3513a4a090b19401b2b20019

Observation 6240a8fd-9101-4ed3-8a5b-431a9dbdad67 · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 22

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:06:49.529175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.744207Z digest=sha256:ea9e8fccaeedfcbfd080b6d40d2b48a12d7c6dfbba6c5a77da971fbc87b0c146

Observation 8114042d-1ee5-49a4-b679-6dce0a64897c · outbound

This paper cites Moser, Nachrichten der Akademie der Wissenschaften in G¨ ottingen.

Combining Machine Learning with Recurrence Analysis for resonance detection Moser, Nachrichten der Akademie der Wissenschaften in G¨ ottingen

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.513879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.748442Z digest=sha256:5fdc2961438593397a761b4085650dd246aaee2dbbd512a90b9bb2b9834dfde1

Observation fb235b0c-8372-4c8a-9b43-0f06bd14a686 · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:06:49.498705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.753090Z digest=sha256:2cf5ea16af94b6eb1c096b613faf36ad5f4d07e6044c852cd962b3da23ed6483

Observation bf78dab6-0aaf-40a0-91fb-5c8a01de0ce0 · outbound

This paper cites How to avoid potential pitfalls in recurrence plot based data analysis.

Combining Machine Learning with Recurrence Analysis for resonance detection How to avoid potential pitfalls in recurrence plot based data analysis

Reference 25

Resolution
metadata mismatch
local_arxiv, observed 2026-08-11T00:06:48.994012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.757672Z digest=sha256:937d0becc013ccd583d00f1ff5899e883494f434b4f901e9575219480103932b

Observation 7a5328c8-c637-4fdf-82ca-304014d156e1 · outbound

This paper cites Recurrence Analysis as a tool to study chaotic dynamics of extreme mass ratio inspiral in signal with noise.

Combining Machine Learning with Recurrence Analysis for resonance detection Recurrence Analysis as a tool to study chaotic dynamics of extreme mass ratio inspiral in signal with noise

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-11T00:06:48.762590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:06:48.762590Z digest=sha256:fb8e26eec962677aa89e3e60704aac7ec4efbd28c947e2d9397c0d0a36f577e6

Observation b2bb4344-5eea-4c34-ad02-0a69d502e482 · outbound

This paper cites Transition from Regular to Chaotic Circulation in Magnetized Coronae near Compact Objects.

Combining Machine Learning with Recurrence Analysis for resonance detection Transition from Regular to Chaotic Circulation in Magnetized Coronae near Compact Objects

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T00:06:48.767417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:06:48.767417Z digest=sha256:a4a340598a4f05fb76970dbbf3fc6e6cd94b76db82fa87e6732149004b8ca209

Observation 6afd78a7-57a5-4f9c-92f0-ae6936c4c5c7 · outbound

This paper cites Takens, in Dynamical Systems and Turbulence, War- wick 1980, edited by D.

Combining Machine Learning with Recurrence Analysis for resonance detection Takens, in Dynamical Systems and Turbulence, War- wick 1980, edited by D

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.484383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.772637Z digest=sha256:d202baf2ef50b56fdec68569a12ef45d4acfa0021f1be73b18d9fa92a2a98f58

Observation 395d7628-b97d-409d-8752-bfae383b2a58 · outbound

This paper cites Hochreiter and J.

Combining Machine Learning with Recurrence Analysis for resonance detection Hochreiter and J

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.468975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.777340Z digest=sha256:62dc203841753324c252cbbaf05f1af22d69fd5f08dadb818cbc2cbe9157996c

Observation db475c41-8197-4523-a69c-80a0e2aa4b1b · outbound

This paper cites Long Short-Term Memory for Early Warning Detection of Gravitational Waves.

Combining Machine Learning with Recurrence Analysis for resonance detection Long Short-Term Memory for Early Warning Detection of Gravitational Waves

Reference 30

Resolution
verified exact
local_arxiv, observed 2026-08-11T00:06:48.935226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.782349Z digest=sha256:2f372d17774c255f1df99da3aec2fb41800d1a7913ee88190ddbd53b193bac82

Observation 08864628-220f-474d-8995-fcdd925b02c1 · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:06:49.453862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.793967Z digest=sha256:0c51a61d3fb172eed5ddd5ab92d85d69efd70ea8e7331351e5e88f7ae0d485f5

Observation 79cc8923-4dd8-4ca0-90cc-9ab5b623d66a · outbound

This paper cites Morbidelli, Modern celestial mechanics: aspects of solar system dynamics , 1st ed.

Combining Machine Learning with Recurrence Analysis for resonance detection Morbidelli, Modern celestial mechanics: aspects of solar system dynamics , 1st ed

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.440556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.799462Z digest=sha256:816cd4d194f8104c67bf6f3a9fce2bba103c818423f573a4abcf02ee40678c3f

Observation a758e7f0-0ffa-403a-be39-939dcb2f6d25 · outbound

This paper cites Reichl, The Transition to Chaos: Conservative Clas- sical Systems and Quantum Manifestations , Institute for Nonlinear Science (Springer, 2004).

Combining Machine Learning with Recurrence Analysis for resonance detection Reichl, The Transition to Chaos: Conservative Clas- sical Systems and Quantum Manifestations , Institute for Nonlinear Science (Springer, 2004)

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.426531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.804496Z digest=sha256:c2d8fd6ad7690414a97421e358c3c3fdd2d2762ff2d08092a712e3d3ce947a5e

Observation 22b39090-8601-4bd9-bcfe-0e06e1e5776e · outbound

This paper cites Chaotic motion in the Johannsen-Psaltis spacetime.

Combining Machine Learning with Recurrence Analysis for resonance detection Chaotic motion in the Johannsen-Psaltis spacetime

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-08-11T00:06:48.910738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.809376Z digest=sha256:cb350f14f340fb0d15513d2744a0bd87e7953ae53e230bfc28dfe948c2dde7bf

Observation 345f318f-222c-41ac-94c0-4a9a9d687893 · outbound

This paper cites Lukes-Gerakopoulos, N.

Combining Machine Learning with Recurrence Analysis for resonance detection Lukes-Gerakopoulos, N

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.411889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.814901Z digest=sha256:00a68b5aef5a208bd5048fafbdfeae5c40623faf6e3c1e9f7c9b1f3bbc3406b9

Observation a5587e73-d196-475d-8280-b525d9a6eb11 · outbound

This paper cites Froeschl´ e, M.

Combining Machine Learning with Recurrence Analysis for resonance detection Froeschl´ e, M

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.395518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.820234Z digest=sha256:e930def977617c5e665cdcd1be0586f80b625165f177896da627823afe9c2aae

Observation b222eadb-1480-4ece-9c5c-8db596fe775c · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Combining Machine Learning with Recurrence Analysis for resonance detection Adam: A Method for Stochastic Optimization

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T00:06:48.825399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:06:48.825399Z digest=sha256:ea57a2086adfe08b664ab9939fec865b845aafcd5b7569368dd45c222c22cb17

Observation 47b87d5c-644b-4ba7-a0e0-0003bad91c1c · outbound

This paper cites Sukov´ a, M.

Combining Machine Learning with Recurrence Analysis for resonance detection Sukov´ a, M

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.378657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.830380Z digest=sha256:5427b54b64ae143648a6c61b046f700b018d94e05a4932fc8a52df7758f1d62b

Observation 58b99189-6581-4172-ae08-cd48c23d0f25 · outbound

This paper cites Hegger, H.

Combining Machine Learning with Recurrence Analysis for resonance detection Hegger, H

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.363206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.835227Z digest=sha256:66f87a6c87a9e9b598d01c3d7a57cd2c32340621cda21334a4b0d32f2a8e5fec

Observation 59880a56-da3a-4ced-85a1-98bd4b4bba16 · outbound

This paper cites Marwan, Commandline recurrence plots (2006), https://tocsy.pik-potsdam.de/commandline-rp.

Combining Machine Learning with Recurrence Analysis for resonance detection Marwan, Commandline recurrence plots (2006), https://tocsy.pik-potsdam.de/commandline-rp

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.347559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.840011Z digest=sha256:4af721b3a9e1ea5067bc7528e2eafa64d146d973ba0557ca06a97eb0a44432aa

Observation ac0d24bf-97b3-4ebe-8684-6a0a85b45163 · outbound

This paper cites Marwan, Recurrence plots and cross recurrence plots (2024), http://www.recurrence-plot.tk.

Combining Machine Learning with Recurrence Analysis for resonance detection Marwan, Recurrence plots and cross recurrence plots (2024), http://www.recurrence-plot.tk

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.332112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.844673Z digest=sha256:57486d438c3cf6d46a1285271a836f712a39de86f7591357820c3c11a4708e5a

Pith citing papers

Observation d0efcb1f-3d96-4d11-ae96-38ca0f59e6b0 · inbound

Combining Machine Learning with Recurrence Analysis for resonance detection cites this paper.

Combining Machine Learning with Recurrence Analysis for resonance detection Combining Machine Learning with Recurrence Analysis for resonance detection

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-11T00:06:49.315940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.633994Z digest=sha256:d80a199d7c4ebe23c43b7efb6ae7ac4bae3aa21fa20369329d90cead282993e4