Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram | Paper Citation Record

Observation a6eaf452-8bc0-4f65-bbe1-9c1d462ec6c0 · outbound

This paper cites Transfer learning for BCIs.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Transfer learning for BCIs

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Observation 26f6609f-4622-4c06-b2ad-ddd5c757b6bb · outbound

This paper cites Bayesian learning for EEG analysis.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Bayesian learning for EEG analysis

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This paper cites The largest eeg-based bci reproducibility study for open science: the moabb benchmark.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram The largest eeg-based bci reproducibility study for open science: the moabb benchmark

Reference 3

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This paper cites Sculley, Sebastian Nowozin, Joshua V.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Sculley, Sebastian Nowozin, Joshua V

Reference 4

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Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Unresolved cited work

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Observation ba7f047e-b1dc-4598-a1c5-40e1bf2a41e9 · outbound

This paper cites Murphy.Probabilistic Machine Learning: An Introduction.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Murphy.Probabilistic Machine Learning: An Introduction

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This paper cites Bishop.Pattern Recognition and Machine Learning.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Bishop.Pattern Recognition and Machine Learning

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This paper cites Bishop and Hugh Bishop.Deep Learning: Foundations and Concepts.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Bishop and Hugh Bishop.Deep Learning: Foundations and Concepts

Reference 8

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This paper cites Murphy.Probabilistic Machine Learning: Advanced Topics.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Murphy.Probabilistic Machine Learning: Advanced Topics

Reference 9

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Observation 5f8ccd4c-019e-4dae-8ff3-c047dcbeeeb5 · outbound

This paper cites Chapman and Hall/CRC, 2 edition, 2020.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Chapman and Hall/CRC, 2 edition, 2020

Reference 10

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Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Unresolved cited work

Reference 11

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Observation a17c6d31-5ba9-438e-964a-cae5b7ab9eef · outbound

This paper cites Duda, Peter E.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Duda, Peter E

Reference 12

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This paper cites Weinberger.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Weinberger

Reference 13

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This paper cites Chapman & Hall/CRC Press, Boca Raton, FL and London, 1st edition, 2021.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Chapman & Hall/CRC Press, Boca Raton, FL and London, 1st edition, 2021

Reference 14

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This paper cites Hedges, Julian P.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Hedges, Julian P

Reference 15

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This paper cites Moabb: trustworthy algorithm benchmarking for bcis.Journal of Neural Engineering, 15(6):066011, 9 2018.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Moabb: trustworthy algorithm benchmarking for bcis.Journal of Neural Engineering, 15(6):066011, 9 2018

Reference 16

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This paper cites Topological superconductivity in tripartite superconductor-ferromagnet-semiconductor nanowires.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Topological superconductivity in tripartite superconductor-ferromagnet-semiconductor nanowires

Reference 17

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Observation 21cff2df-71ca-4eb0-9cbe-8075e3a50357 · outbound

This paper cites Motor imagery under distraction— an open ac- cess bci dataset.Frontiers in Neuroscience, Volume 14 - 2020, 2020.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Motor imagery under distraction— an open ac- cess bci dataset.Frontiers in Neuroscience, Volume 14 - 2020, 2020

Reference 18

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Observation 798b269a-bf0e-4250-8182-6540f64e5c69 · outbound

This paper cites A multi-paradigm EEG dataset for studying upper limb rehabilitation exercises.Scientific Data, 12(1):1877, 2025.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram A multi-paradigm EEG dataset for studying upper limb rehabilitation exercises.Scientific Data, 12(1):1877, 2025

Reference 19

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Observation 44227ce7-cb0d-4fae-ba8c-6b98c10d269c · outbound

This paper cites Eeg datasets for motor imagery brain–computer interface.GigaScience, 6(7):gix034, 5 2017.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Eeg datasets for motor imagery brain–computer interface.GigaScience, 6(7):gix034, 5 2017

Reference 20

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This paper cites Experimenters’ influence on mental-imagery based brain-computer interface user training.International Journal of Human-Computer Studies, 149:102603, 2021.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Experimenters’ influence on mental-imagery based brain-computer interface user training.International Journal of Human-Computer Studies, 149:102603, 2021

Reference 21

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Observation ee4362a7-7db3-44c1-895e-d4cd9ec68ca9 · outbound

This paper cites When should MI-BCI feature optimization include prior knowledge, and which one?Brain-Computer Interfaces, 9(2):115–128, 4 2022.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram When should MI-BCI feature optimization include prior knowledge, and which one?Brain-Computer Interfaces, 9(2):115–128, 4 2022

Reference 22

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Observation 9fe03cd6-4119-4ed3-a4b0-08f48d0b0011 · outbound

This paper cites Integrat- ing simultaneous motor imagery and spatial attention for eeg-bci control.IEEE Transactions on Biomedical Engineering, 71(1):282–294, 2024.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Integrat- ing simultaneous motor imagery and spatial attention for eeg-bci control.IEEE Transactions on Biomedical Engineering, 71(1):282–294, 2024

Reference 23

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This paper cites Beamforming in noninvasive brain–computer interfaces.IEEE Transactions on Biomedical Engineering, 56 (4):1209–1219, 2009.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Beamforming in noninvasive brain–computer interfaces.IEEE Transactions on Biomedical Engineering, 56 (4):1209–1219, 2009

Reference 24

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Observation 3ad1ac8d-177d-4d01-8540-2104acdd1c47 · outbound

This paper cites Dataset combining EEG, eye- tracking, and high-speed video for ocular activity analysis across BCI paradigms.Sci- entific Data, 12(1):587, 2025.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Dataset combining EEG, eye- tracking, and high-speed video for ocular activity analysis across BCI paradigms.Sci- entific Data, 12(1):587, 2025

Reference 25

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This paper cites HEFMI-ICH: a hybrid EEG-fNIRS motor imagery dataset for brain-computer interface in intracerebral hemorrhage.Scientific Data, 12(1):1816, 2025.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram HEFMI-ICH: a hybrid EEG-fNIRS motor imagery dataset for brain-computer interface in intracerebral hemorrhage.Scientific Data, 12(1):1816, 2025

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This paper cites Transfer learning promotes acquisition of individual bci skills.PNAS Nexus, 3(2): pgae076, 02 2024.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Transfer learning promotes acquisition of individual bci skills.PNAS Nexus, 3(2): pgae076, 02 2024

Reference 27

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This paper cites Eeg dataset and openbmi toolbox for three bci paradigms: an investigation into bci illiteracy.GigaScience, 8(5):giz002, 1 2019.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Eeg dataset and openbmi toolbox for three bci paradigms: an investigation into bci illiteracy.GigaScience, 8(5):giz002, 1 2019

Reference 28

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This paper cites EEG datasets of stroke patients, 12 2022.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram EEG datasets of stroke patients, 12 2022

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This paper cites An EEG Motor Imagery Dataset for Brain Computer Interface in Acute Stroke Patients.Scientific Data, 11(1):131,.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram An EEG Motor Imagery Dataset for Brain Computer Interface in Acute Stroke Patients.Scientific Data, 11(1):131,

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Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Unresolved cited work

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This paper cites Deep learning with convolutional neural networks for eeg decoding and visu- alization.Human Brain Mapping, 38(11):5391–5420, 2017.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Deep learning with convolutional neural networks for eeg decoding and visu- alization.Human Brain Mapping, 38(11):5391–5420, 2017

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This paper cites Open access dataset for eeg+nirs single-trial classification.IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(10): 1735–1745, 2017.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Open access dataset for eeg+nirs single-trial classification.IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(10): 1735–1745, 2017

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This paper cites Stieger, Stephen A.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Stieger, Stephen A

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This paper cites Evaluation of eeg oscillatory patterns and cognitive process during simple and compound limb motor imagery.PLOS ONE, 9(12):1–19, 12 2014.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Evaluation of eeg oscillatory patterns and cognitive process during simple and compound limb motor imagery.PLOS ONE, 9(12):1–19, 12 2014

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This paper cites A multi-day and high-quality EEG dataset for motor imagery brain-computer interface.Scientific Data, 12(1):488, 2025.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram A multi-day and high-quality EEG dataset for motor imagery brain-computer interface.Scientific Data, 12(1):488, 2025

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This paper cites Relative power correlates with the decoding performance of motor imagery both across time and subjects.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Relative power correlates with the decoding performance of motor imagery both across time and subjects

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This paper cites Cambridge University Press, 2020.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Cambridge University Press, 2020

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Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Springer Series in Statistics

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This paper cites Panel usages ´ electrodomestiques ann´ ee 6, 3 2026.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Panel usages ´ electrodomestiques ann´ ee 6, 3 2026

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This paper cites Martin, Ravin Kumar, and Junpeng Lao.Bayesian Modeling and Computation in Python.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Martin, Ravin Kumar, and Junpeng Lao.Bayesian Modeling and Computation in Python

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This paper cites OptunaHub: A Platform for Black-Box Optimization.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram OptunaHub: A Platform for Black-Box Optimization

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Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Riley, Jayne F

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This paper cites Chapman and Hall/CRC, 1st edition, 2019.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Chapman and Hall/CRC, 1st edition, 2019

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Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram Cambridge University Press, 2006

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This paper cites URLhttps://www.pnas.org/doi/abs/10.1073/pnas.

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram URLhttps://www.pnas.org/doi/abs/10.1073/pnas

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