The more, the better? Evaluating the role of EEG preprocessing for deep learning applications | Paper Citation Record

Observation 576b6514-1bf9-48f1-8516-1eb7d7d8d7e4 · outbound

This paper cites A com- prehensive review of EEG-based brain-computer interface paradigms,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications A com- prehensive review of EEG-based brain-computer interface paradigms,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:01.097425Z

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.

Observation ad80c38b-e0d3-4591-a74f-4c6cd821c6a7 · outbound

This paper cites EEG based emotion recognition: A tutorial and review,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications EEG based emotion recognition: A tutorial and review,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:01.081060Z

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.

Observation d93892f4-3593-413d-a3b0-d62f75d4b135 · outbound

This paper cites Sleep stage classification using EEG signal analysis: a compre- hensive survey and new investigation,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Sleep stage classification using EEG signal analysis: a compre- hensive survey and new investigation,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:01.064285Z

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.

Observation 04200037-8c71-4fba-95b5-9c70456c35a5 · outbound

This paper cites Machine learning for predicting epileptic seizures using EEG signals: A review,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Machine learning for predicting epileptic seizures using EEG signals: A review,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:01.048803Z

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.

Observation 1046fc5c-19a0-4991-b4a7-8ca73a129cc1 · outbound

This paper cites Survey of machine learning techniques in the analysis of EEG signals for Parkinson’s disease: A systematic review,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Survey of machine learning techniques in the analysis of EEG signals for Parkinson’s disease: A systematic review,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:01.032887Z

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.

Observation be62f6fe-2b88-4ea6-a097-2d26338964bd · outbound

This paper cites Deep learning in the EEG diagnosis of Alzheimer’s disease,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Deep learning in the EEG diagnosis of Alzheimer’s disease,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:01.017284Z

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.

Observation 10b2dcc7-07d6-48b3-8493-6da2e75a68ef · outbound

This paper cites Deep learning for electroen- cephalogram (EEG) classification tasks: a review,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Deep learning for electroen- cephalogram (EEG) classification tasks: a review,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:01.001484Z

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.

Observation 4da073d5-7222-4b4c-b65a-8a234f6ec321 · outbound

This paper cites Deep learning,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Deep learning,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T11:17:59.760787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e270e2b9-c2f1-4885-8681-904a7042db7d · outbound

This paper cites EEG datasets for health- care: a scoping review,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications EEG datasets for health- care: a scoping review,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.975887Z

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.

Observation bccaa905-c4da-423b-9cae-58085ffbfd3b · outbound

This paper cites The harvard automated processing pipeline for electroen- cephalography (HAPPE): standardized processing software for devel- opmental and high-artifact data,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications The harvard automated processing pipeline for electroen- cephalography (HAPPE): standardized processing software for devel- opmental and high-artifact data,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.962092Z

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.

Observation ec259ad9-6efe-42b8-a796-f82cf077525e · outbound

This paper cites Automagic: Standardized preprocessing of big EEG data,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Automagic: Standardized preprocessing of big EEG data,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.946980Z

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.

Observation 9b9108df-cd98-421e-8fb7-2d17c7b9e430 · outbound

This paper cites BID- SAlign: a library for automatic merging and preprocessing of multiple EEG repositories,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications BID- SAlign: a library for automatic merging and preprocessing of multiple EEG repositories,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.933467Z

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.

Observation 934d1022-cfa1-471f-8da1-d416010fbab8 · outbound

This paper cites Self-supervised learning for electroencephalography,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Self-supervised learning for electroencephalography,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.919418Z

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.

Observation 83a13807-47de-42e6-914b-770bf004b433 · outbound

This paper cites Deep learning-based electroencephalography analysis: a systematic review,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Deep learning-based electroencephalography analysis: a systematic review,

Reference 14

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T11:18:00.905427Z

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.

Observation bb920da9-c558-4621-afdb-e656a488c5ec · outbound

This paper cites On the classification of SSVEP-based dry-EEG signals via convolutional neural networks,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications On the classification of SSVEP-based dry-EEG signals via convolutional neural networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.891682Z

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.

Observation 3686fed1-af74-45cc-8d46-1de206d86e09 · outbound

This paper cites Eeg-signals based cognitive workload detection of vehicle driver using deep learning,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Eeg-signals based cognitive workload detection of vehicle driver using deep learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.875910Z

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.

Observation 2bbbc1cb-3c64-4359-b72a-db0b2fbc9b22 · outbound

This paper cites Towards best practice of interpreting deep learning models for EEG-based brain computer interfaces,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Towards best practice of interpreting deep learning models for EEG-based brain computer interfaces,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.861654Z

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.

Observation d3f43724-738a-4d6d-8c20-8656d1b12cbe · outbound

This paper cites Cross-participant EEG-based assessment of cognitive work- load using multi-path convolutional recurrent neural networks,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Cross-participant EEG-based assessment of cognitive work- load using multi-path convolutional recurrent neural networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.846404Z

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.

Observation 5d76d852-372a-463a-a265-7d3985e1bfde · outbound

This paper cites On EEG preprocessing role in deep learning effectiveness for mental workload classification,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications On EEG preprocessing role in deep learning effectiveness for mental workload classification,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.831603Z

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.

Observation eace491b-b857-4e8e-a6a0-c8337a196ce2 · outbound

This paper cites The OpenNeuro resource for sharing of neuroscience data,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications The OpenNeuro resource for sharing of neuroscience data,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.815916Z

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.

Observation 94aad03d-7fdc-4cab-b017-f7af82f8f027 · outbound

This paper cites American clinical neurophysiology society guideline 1: minimum technical requirements for performing clinical electroencephalography,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications American clinical neurophysiology society guideline 1: minimum technical requirements for performing clinical electroencephalography,

Reference 21

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T11:18:00.800028Z

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.

Observation 3b5e5c56-84c4-47b1-a0e9-76046a29f58d · outbound

This paper cites Deep learning techniques for classification of electroencephalogram (EEG) motor imagery (MI) signals: A review,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Deep learning techniques for classification of electroencephalogram (EEG) motor imagery (MI) signals: A review,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.785763Z

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.

Observation 52553a63-8b1a-4a41-955a-179b6f0ef8d7 · outbound

This paper cites A test-retest resting and cognitive state EEG dataset,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications A test-retest resting and cognitive state EEG dataset,

Reference 23

Resolution: verified exact; doi, observed 2026-08-12T11:18:00.158362Z

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.

Observation 0ea35a53-026a-4008-b10e-3183526d9d2b · outbound

This paper cites A dataset of EEG recordings from: Alzheimer’s disease, frontotemporal dementia and healthy subjects,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications A dataset of EEG recordings from: Alzheimer’s disease, frontotemporal dementia and healthy subjects,

Reference 24

Resolution: verified exact; doi, observed 2026-08-12T11:18:00.143989Z

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.

Observation 5bea14a3-ace3-46ea-bc0d-2c25214cf22f · outbound

This paper cites Deep comparisons of neural networks from the EEGNet family,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Deep comparisons of neural networks from the EEGNet family,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.770019Z

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.

Observation c9d04f77-1d62-4bc1-a7af-4b9c981002d8 · outbound

This paper cites Motor imagery decoding using ensemble curriculum learning and collaborative training,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Motor imagery decoding using ensemble curriculum learning and collaborative training,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.754871Z

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.

Observation 97b511f0-2d2c-4e69-b030-1b39ff8aaf67 · outbound

This paper cites UC San Diego resting state EEG data from patients with Parkinson’s disease,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications UC San Diego resting state EEG data from patients with Parkinson’s disease,

Reference 27

Resolution: malformed identifier; no resolver link, observed 2026-08-12T11:17:59.843932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67ac0255-ec88-45d8-a590-09b5f695c133 · outbound

This paper cites EEG: 3-stim auditory oddball and rest in Parkinson’s,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications EEG: 3-stim auditory oddball and rest in Parkinson’s,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.740304Z

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.

Observation 89a386e0-5932-4e77-a759-f1b91267771b · outbound

This paper cites A resting- state EEG dataset for sleep deprivation,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications A resting- state EEG dataset for sleep deprivation,

Reference 29

Resolution: verified exact; doi, observed 2026-08-12T11:18:00.104887Z

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.

Observation 547e351e-7ffa-407c-ab19-9491dd0986b3 · outbound

This paper cites EEG: First episode psychosis vs. control resting task 2,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications EEG: First episode psychosis vs. control resting task 2,

Reference 30

Resolution: verified exact; doi, observed 2026-08-12T11:18:00.090026Z

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.

Observation 0f996ccc-efb3-455e-98bd-741d9e152fad · outbound

This paper cites EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-12T11:17:59.868674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2dd94278-2f43-4817-b25d-b7f6aa0ff308 · outbound

This paper cites An information-maximization approach to blind separation and blind deconvolution,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications An information-maximization approach to blind separation and blind deconvolution,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.716443Z

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.

Observation 32f07be8-28ac-4a06-bc63-c31b3b8222d3 · outbound

This paper cites ICLabel: An automated electroencephalographic independent component classifier, dataset, and website,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications ICLabel: An automated electroencephalographic independent component classifier, dataset, and website,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.701584Z

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.

Observation 82311c9d-3bd4-4aaf-9f95-3dbbaaef68aa · outbound

This paper cites Real-time neuroimaging and cognitive monitoring using wearable dry EEG,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Real-time neuroimaging and cognitive monitoring using wearable dry EEG,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.686648Z

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.

Observation 34c30d11-1e67-47b4-8717-27ffc10877bb · outbound

This paper cites Distortions in EEG interregional phase synchrony by spherical spline interpolation: causes and remedies,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Distortions in EEG interregional phase synchrony by spherical spline interpolation: causes and remedies,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.671373Z

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.

Observation 16738280-1534-4083-aac3-534a3330e5bb · outbound

This paper cites On the effects of data normalization for domain adaptation on EEG data,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications On the effects of data normalization for domain adaptation on EEG data,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.655635Z

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.

Observation f8749323-58a3-4b86-ac53-fca85caf23bb · outbound

This paper cites SelfEEG: A Python library for self-supervised learning in electroen- cephalography,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications SelfEEG: A Python library for self-supervised learning in electroen- cephalography,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.639992Z

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.

Observation 88f7b0a4-c6f1-4cd3-af1d-792e1e45dbde · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Pytorch: An imperative style, high-performance deep learning library,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.625730Z

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.

Observation 7b5588b0-f7ee-4048-9453-2fd33d6d35c4 · outbound

This paper cites SciPy 1.0: fundamental algorithms for scientific computing in python,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications SciPy 1.0: fundamental algorithms for scientific computing in python,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.610369Z

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.

Observation 4eb03181-7235-47a9-8b2e-a18944f9dbe6 · outbound

This paper cites Seaborn: statistical data visualization,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Seaborn: statistical data visualization,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.594831Z

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.

Observation 5d2a2976-24ab-4d81-9bd5-cf6c2a78d6b0 · outbound

This paper cites Statannotations,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Statannotations,

Reference 41

Resolution: verified exact; doi, observed 2026-08-12T11:18:00.074412Z

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.

Observation e41478dc-842a-4902-b5d0-182770d7eae0 · outbound

This paper cites EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-12T11:17:59.919373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02de0333-b97f-4425-a6bb-6c83993e0e34 · outbound

This paper cites Deep learning with convolutional neural networks for EEG decoding and visualization,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Deep learning with convolutional neural networks for EEG decoding and visualization,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.570630Z

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.

Observation 4012269b-ae07-4a87-8d5f-79b1edd43438 · outbound

This paper cites A multi- view CNN with novel variance layer for motor imagery brain computer interface,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications A multi- view CNN with novel variance layer for motor imagery brain computer interface,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.555520Z

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.

Observation 33d7a7ab-046b-4767-a240-97e2137092b7 · outbound

This paper cites Subject-Aware Contrastive Learning for Biosignals.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Subject-Aware Contrastive Learning for Biosignals

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-12T11:17:59.933120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 324e3985-4f41-4bbc-88fc-6da16d260348 · outbound

This paper cites The necessity of leave one subject out (LOSO) cross validation for EEG disease diagnosis,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications The necessity of leave one subject out (LOSO) cross validation for EEG disease diagnosis,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.541232Z

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.

Observation 49be3ce0-19b4-4c0e-82b6-eb3176ef3596 · outbound

This paper cites On over-fitting in model selection and subsequent selection bias in performance evaluation,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications On over-fitting in model selection and subsequent selection bias in performance evaluation,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.527039Z

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.

Observation 5ca31c6a-6f9a-4e69-8739-05d2659192d6 · outbound

This paper cites Adam: A method for stochastic optimization,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Adam: A method for stochastic optimization,

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T11:17:59.947489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 842834f1-b6a9-4985-a476-c6dfcfefd6fd · outbound

This paper cites Individual comparisons by ranking methods,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Individual comparisons by ranking methods,

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T11:17:59.951487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0bc96f6-70b2-440b-bdfc-17b48c5bfbd6 · outbound

This paper cites On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.504284Z

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.

Observation a2171cec-664e-4629-a6de-260753e5bfd1 · outbound

This paper cites A simple sequentially rejective multiple test procedure,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications A simple sequentially rejective multiple test procedure,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-12T11:17:59.961562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f838ac15-61a1-4ad8-8850-a8a5d6de52a7 · outbound

This paper cites The use of ranks to avoid the assumption of normality implicit in the analysis of variance,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications The use of ranks to avoid the assumption of normality implicit in the analysis of variance,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-12T11:17:59.966043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84a2b01f-f3d2-4a5b-947a-fbb553dcd2ff · outbound

This paper cites Statistical comparisons of classifiers over multiple data sets,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Statistical comparisons of classifiers over multiple data sets,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.480944Z

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.

Observation 89052503-e0a3-4b6e-99cc-2956f03c7122 · outbound

This paper cites Model evaluation, model selection, and algorithm selection in machine learning,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Model evaluation, model selection, and algorithm selection in machine learning,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.455928Z

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.

Observation fd352dd1-f90f-4de5-8dac-4d7cf5ee3c69 · outbound

This paper cites The effect of preprocessing techniques, applied to numeric features, on classification algorithms’ performance,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications The effect of preprocessing techniques, applied to numeric features, on classification algorithms’ performance,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.441213Z

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.

Observation d4a82485-99b1-4aa7-a4c2-30ae09eb8c19 · outbound

This paper cites an unresolved cited work.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-12T11:18:00.424658Z

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.

Observation b4319934-59f9-40c4-89ba-5bc17696fdfa · outbound

This paper cites Approximate statistical tests for comparing supervised classification learning algorithms,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Approximate statistical tests for comparing supervised classification learning algorithms,

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T11:17:59.998075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4644152-192a-4a4c-9ffb-ce252795218f · outbound

This paper cites Available: https://doi.org/10.3390/data6020011.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Available: https://doi.org/10.3390/data6020011

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T11:17:59.988504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1fd055e-fbae-4728-94cc-5412f6a97bc2 · outbound

This paper cites Inference for the generalization error,.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Inference for the generalization error,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.409184Z

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.

Observation 547a877a-ac2e-44c3-8bf8-fd0d3af16167 · outbound

This paper cites to(device=‘cuda’).

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications to(device=‘cuda’)

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.394750Z

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.

Observation d2172722-b0d0-4a0e-ba06-90f548e5e52c · outbound

This paper cites an unresolved cited work.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-08-12T11:18:00.379665Z

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.

Observation 38f26943-af72-4c79-bff6-a5ea2bb45cba · outbound

This paper cites Data Partition.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Data Partition

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:18:00.364287Z

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.

Observation b5896c20-8044-4dc4-93ef-20eac53bf9fe · outbound

This paper cites Available: http://jmlr.org/papers/v7/demsar06a.html.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Available: http://jmlr.org/papers/v7/demsar06a.html

Reference 2006

Resolution: unresolved; no resolver link, observed 2026-08-12T11:17:59.975266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 725c53e1-2f40-4faf-8677-cb4f41fcf09f · outbound

This paper cites Available: https://doi.org/10.18112/openneuro.ds003490.

The more, the better? Evaluating the role of EEG preprocessing for deep learning applications Available: https://doi.org/10.18112/openneuro.ds003490

Reference 2021

Resolution: verified exact; doi, observed 2026-08-12T11:18:00.119986Z

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.

Coverage vector

Reference resolution

Outbound references

Pith citing papers