Paper Citation Record · LEDGER

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning

As of 11 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:2507.07511.

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

pith.paper-citation-record.v1
2507.07511 v2

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:43:12.035504Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:43:09.081553Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T18:43:12.135532Z

Reference resolution

23 of 23 outbound references displayed

verified exact0
verified fuzzy19
unresolved3
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation de8fb701-7b1f-4632-a481-c58f5c78f71f · outbound

This paper cites Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning

Reference 1

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Source-reported events for the cited work

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Observation 17ac574d-807d-46af-9b2b-1b145da374d5 · outbound

This paper cites Specifically, we use the datasets from Steyrl et al.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Specifically, we use the datasets from Steyrl et al

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:16.793805Z

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Observation 2c7e0805-34d3-4b27-bf38-67445ea6a545 · outbound

This paper cites We see that MDRM is generally under- confident (accuracy higher than confidence), while the Deep Learning methods are all overconfident.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning We see that MDRM is generally under- confident (accuracy higher than confidence), while the Deep Learning methods are all overconfident

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:16.593046Z

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Observation ad8d0bb3-ebfe-45fd-a111-584ad5cd2563 · outbound

This paper cites an unresolved cited work.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Unresolved cited work

Reference 4

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Observation 341af491-3483-4f2e-a89d-3fdc505fb35d · outbound

This paper cites We show that it gives better calibrated uncertainty estimates than MDRM, without affecting the classification performance.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning We show that it gives better calibrated uncertainty estimates than MDRM, without affecting the classification performance

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:16.149640Z

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Observation cf0c5e79-5bc0-433a-8abd-fe44362cb3f2 · outbound

This paper cites Un- certainty quantification for cross-subject motor imagery classification,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Un- certainty quantification for cross-subject motor imagery classification,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:15.888716Z

Source-reported events for the cited work

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Observation 0d242e13-c395-4e6a-9188-a683ad8dc8eb · outbound

This paper cites Robust mo- tor imagery tasks classification approach using bayesian neural network,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Robust mo- tor imagery tasks classification approach using bayesian neural network,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:15.589705Z

Source-reported events for the cited work

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Observation fe5fdcd6-da81-4448-a93b-78a19c5dc619 · outbound

This paper cites Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review

Reference 8

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Observation cdc07544-6fbc-44bc-973f-4d4f398892e4 · outbound

This paper cites Opti- mizing spatial filters for robust eeg single-trial analy- sis,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Opti- mizing spatial filters for robust eeg single-trial analy- sis,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:15.338418Z

Source-reported events for the cited work

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Observation 0b5c4697-b95b-46be-be58-192f43350c76 · outbound

This paper cites Multiclass brain–computer interface classification by riemannian geometry,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Multiclass brain–computer interface classification by riemannian geometry,

Reference 10

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Source-reported events for the cited work

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Observation 5a8420c4-400e-44f1-83a3-9db4bd05feb6 · outbound

This paper cites Uncertainty estimation using a single deep deterministic neural network,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Uncertainty estimation using a single deep deterministic neural network,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:14.714420Z

Source-reported events for the cited work

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Observation 34b663b7-3d60-429e-90a1-e1eb51834a97 · outbound

This paper cites Deep learn- ing with convolutional neural networks for eeg decoding and visualization,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Deep learn- ing with convolutional neural networks for eeg decoding and visualization,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:14.469822Z

Source-reported events for the cited work

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Observation 0d8fc276-c268-4872-ba7a-00fbc4cdf5a1 · outbound

This paper cites Random forests in non-invasive sensorimotor rhythm brain-computer interfaces: a prac- tical and convenient non-linear classifier,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Random forests in non-invasive sensorimotor rhythm brain-computer interfaces: a prac- tical and convenient non-linear classifier,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:13.984436Z

Source-reported events for the cited work

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Observation d9d11451-4464-49c2-ad3d-9d8320e68910 · outbound

This paper cites A fully automated trial selection method for optimization of motor imagery based brain-computer interface,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning A fully automated trial selection method for optimization of motor imagery based brain-computer interface,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:13.567414Z

Source-reported events for the cited work

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Observation c7435929-8adf-482d-8bb5-315442887144 · outbound

This paper cites Brain– computer communication: motivation, aim, and impact of exploring a virtual apartment,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Brain– computer communication: motivation, aim, and impact of exploring a virtual apartment,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:13.414890Z

Source-reported events for the cited work

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Observation e56ba48a-0253-4958-b6e3-9bc5c6b6029f · outbound

This paper cites Review of the bci competition iv,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Review of the bci competition iv,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:13.266737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation aeaba0c2-9c3b-472e-a1d4-bd858b74f6e5 · outbound

This paper cites Mother of all bci benchmarks,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Mother of all bci benchmarks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:13.158273Z

Source-reported events for the cited work

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Observation f2d7a0a8-2eb0-4685-a192-7ebcf3086519 · outbound

This paper cites On calibration of modern neural networks,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning On calibration of modern neural networks,

Reference 18

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Source-reported events for the cited work

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Observation 631b02e9-aecd-4b53-b460-72e3f9ee5606 · outbound

This paper cites Deep learning with convolutional neural net- works for eeg decoding and visualization: Convolu- tional neural networks in eeg analysis,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Deep learning with convolutional neural net- works for eeg decoding and visualization: Convolu- tional neural networks in eeg analysis,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:12.849423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 416ba59a-3ab4-47c9-beab-18d4647829a4 · outbound

This paper cites Simple and scalable predictive un- certainty estimation using deep ensembles,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Simple and scalable predictive un- certainty estimation using deep ensembles,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:12.689303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d321912e-b547-4446-952b-690dedede69e · outbound

This paper cites Overconfidence is Key: Verbalized Uncertainty Evaluation in Large Language and Vision-Language Models.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Overconfidence is Key: Verbalized Uncertainty Evaluation in Large Language and Vision-Language Models

Reference 21

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Source-reported events for the cited work

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Observation 57653d9c-0b2e-49f2-ae43-d49d98040df4 · outbound

This paper cites Assessment and comparison of prog- nostic classification schemes for survival data,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Assessment and comparison of prog- nostic classification schemes for survival data,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:12.563953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d316c284-8474-47d4-8010-fdf22bce9008 · outbound

This paper cites Bayesian opportunities for brain–computer interfaces: Enhancement of the existing classification algorithms and out-of-domain detection,.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Bayesian opportunities for brain–computer interfaces: Enhancement of the existing classification algorithms and out-of-domain detection,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:43:12.415870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation de8fb701-7b1f-4632-a481-c58f5c78f71f · inbound