Paper Citation Record · LEDGER

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data

As of 13 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2412.17833.

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

pith.paper-citation-record.v1
2412.17833 v1

Coverage vector

measured 31 of 31 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-11T15:38:30.209160Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

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External citation measurements

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Outbound references

Observation 24a21682-ae53-45c5-ac7b-5c4ce77e8eac · outbound

This paper cites Progress in brain computer in- terface: Challenges and opportunities,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Progress in brain computer in- terface: Challenges and opportunities,

Reference 1

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Observation 565f5e17-98fd-4f73-9e85-d7508e74cf72 · outbound

This paper cites A novel deep learning scheme for motor imagery eeg decoding based on spatial representation fusion,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data A novel deep learning scheme for motor imagery eeg decoding based on spatial representation fusion,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:38:31.555099Z

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Observation 12a3ea00-6cdc-493f-b71c-71c6633d496e · outbound

This paper cites Fuzzy temporal convolutional neural networks in p300-based brain–computer interface for smart home interaction,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Fuzzy temporal convolutional neural networks in p300-based brain–computer interface for smart home interaction,

Reference 3

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Observation c3dfa205-e1d7-4ba4-89e2-a3e0b64cd0bc · outbound

This paper cites Improving speller bci performance using a cluster-based under-sampling method,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Improving speller bci performance using a cluster-based under-sampling method,

Reference 4

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Observation 7f0712be-e581-419a-a9d5-08bd8cd98b80 · outbound

This paper cites Under-sampling and classification of p300 single-trials using self-organized maps and deep neural networks for a speller bci,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Under-sampling and classification of p300 single-trials using self-organized maps and deep neural networks for a speller bci,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:38:31.505883Z

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Observation ef34b540-7408-4abb-bb45-18b32a3a5db6 · outbound

This paper cites The application of transfer learning in p300 detection,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data The application of transfer learning in p300 detection,

Reference 6

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Observation 99dfae93-2e36-462e-8cb6-7ccb1d4e9189 · outbound

This paper cites Cross- domain mlp and cnn transfer learning for biological signal processing: Eeg and emg,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Cross- domain mlp and cnn transfer learning for biological signal processing: Eeg and emg,

Reference 7

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Observation 3be887ae-0b38-4d69-84fc-2a19bfa82439 · outbound

This paper cites A deep transfer convolutional neural network framework for eeg signal classification,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data A deep transfer convolutional neural network framework for eeg signal classification,

Reference 8

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Observation c22b3f31-fc36-4b58-bfd1-c17e2a1773b6 · outbound

This paper cites Classification and transfer learning of eeg during a kinesthetic motor imagery task using deep convolutional neural networks,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Classification and transfer learning of eeg during a kinesthetic motor imagery task using deep convolutional neural networks,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:38:31.240120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d0e7b36f-bf47-4ae7-8b5f-69d02862ea7f · outbound

This paper cites Adaptive transfer learning for eeg motor imagery classification with deep convolutional neural network,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Adaptive transfer learning for eeg motor imagery classification with deep convolutional neural network,

Reference 10

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Observation cebb38aa-5d15-4018-ad4a-ba1908d4fb60 · outbound

This paper cites Accelerating minibatch stochastic gradient descent using stratified sampling,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Accelerating minibatch stochastic gradient descent using stratified sampling,

Reference 11

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Observation 4085d632-b9d5-4a3c-841a-b038749bd88a · outbound

This paper cites Posterior transfer learning with active sampling,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Posterior transfer learning with active sampling,

Reference 12

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Observation bad64d49-1c39-4758-8c73-befd9b0a93b2 · outbound

This paper cites Imbalanced data classification: Using transfer learning and active sampling,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Imbalanced data classification: Using transfer learning and active sampling,

Reference 13

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Observation af7d61a2-4362-4470-80b7-7179f64ea6d5 · outbound

This paper cites Positive-negative momen- tum: Manipulating stochastic gradient noise to improve generalization,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Positive-negative momen- tum: Manipulating stochastic gradient noise to improve generalization,

Reference 14

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Observation 79ecbeaf-5fd7-4601-968f-6b11aaa8c536 · outbound

This paper cites Kulesza and B.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Kulesza and B

Reference 15

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Observation 801e5517-e3a0-4ff7-b02f-40e8858f1020 · outbound

This paper cites k-dpps: Fixed-size determinantal point processes,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data k-dpps: Fixed-size determinantal point processes,

Reference 16

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This paper cites Determinantal point processes for machine learning,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Determinantal point processes for machine learning,

Reference 17

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Observation 8666f203-a1b5-4ac1-b490-d3586399b944 · outbound

This paper cites Diverse mini-batch Active Learning.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Diverse mini-batch Active Learning

Reference 18

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This paper cites Determinantal Point Processes for Mini-Batch Diversification.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Determinantal Point Processes for Mini-Batch Diversification

Reference 19

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Observation 0d3abff9-bfb5-4a24-a15e-72909d99b797 · outbound

This paper cites Active mini-batch sampling using repulsive point processes,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Active mini-batch sampling using repulsive point processes,

Reference 20

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Observation e00c5114-1ab1-497c-8731-832512972d19 · outbound

This paper cites A comparison of methods for generating poisson disk distributions,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data A comparison of methods for generating poisson disk distributions,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:38:30.905875Z

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Observation 45f1ce1d-f11c-4750-8beb-3cf0f00d9001 · outbound

This paper cites An efficient p300-based brain–computer interface for disabled subjects,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data An efficient p300-based brain–computer interface for disabled subjects,

Reference 22

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This paper cites Perfor- mance evaluation of a p300 brain-computer interface using a kernel extreme learning machine classifier,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Perfor- mance evaluation of a p300 brain-computer interface using a kernel extreme learning machine classifier,

Reference 23

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Observation 91c05001-bc29-43cc-b68f-f9351e1e519c · outbound

This paper cites Deep learning techniques for eeg signal applications–a review,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Deep learning techniques for eeg signal applications–a review,

Reference 24

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Observation b306602f-2a3a-4834-ad5c-99a6b6ca7458 · outbound

This paper cites Brain–computer interfaces for communication and control,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Brain–computer interfaces for communication and control,

Reference 25

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Observation d852b39c-95c2-4548-97f3-3d5fb397ba0a · outbound

This paper cites A gentle introduction and survey on computing with words (cww) methodologies,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data A gentle introduction and survey on computing with words (cww) methodologies,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:38:30.690370Z

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Observation 49df714c-480c-49a7-9872-3622dce626a8 · outbound

This paper cites Towards understanding human functional brain development with explainable artificial intelligence: Challenges and perspectives,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Towards understanding human functional brain development with explainable artificial intelligence: Challenges and perspectives,

Reference 27

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This paper cites Real time recognition of human activities from wearable sensors by evolving classifiers,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Real time recognition of human activities from wearable sensors by evolving classifiers,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:38:30.656343Z

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Observation b635ca6c-39af-4b45-b056-355970f5f116 · outbound

This paper cites Effective brain connectivity for fnirs with fuzzy cog- nitive maps in neuroergonomics,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Effective brain connectivity for fnirs with fuzzy cog- nitive maps in neuroergonomics,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:38:30.606828Z

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Observation 4d44eab8-505e-465b-bc20-cc5f3a4bbd5d · outbound

This paper cites Deep learning towards intelligent vehicle fault diagnosis,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Deep learning towards intelligent vehicle fault diagnosis,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:38:30.487687Z

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Observation f2229d66-af3b-4392-b2b8-82fd3a7f56a1 · outbound

This paper cites Single-trial recognition of video gamer’s expertise from brain haemodynamic and facial emotion re- sponses,.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data Single-trial recognition of video gamer’s expertise from brain haemodynamic and facial emotion re- sponses,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:38:30.376944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

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