[HTML][HTML] Leakage and the reproducibility crisis in machine-learning-based science
S Kapoor, A Narayanan - Patterns, 2023 - cell.com
Machine-learning (ML) methods have gained prominence in the quantitative sciences.
However, there are many known methodological pitfalls, including data leakage, in ML …
However, there are many known methodological pitfalls, including data leakage, in ML …
Achieving Reproducibility in EEG-Based Machine Learning
Despite the inherent complexity of electroencephalogram (EEG) data characterized by its
high dimensionality, artifactual noise, and biological variability, many machine learning (ML) …
high dimensionality, artifactual noise, and biological variability, many machine learning (ML) …
A maximum likelihood perspective of spatial filter design in SSVEP-based BCIs
Z Wang, X Zhao, M Zhang, H Hu - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In steady-state visual-evoked potential (SSVEP) based brain-computer interfaces (BCIs),
existing detection algorithms utilizing spatial filters like task-related component analysis …
existing detection algorithms utilizing spatial filters like task-related component analysis …
Correction to “Designing a Sum of Squared Correlations Framework for Enhancing SSVEP Based BCIs”
GRK Kumar, MR Reddy - IEEE Transactions on Neural …, 2020 - ieeexplore.ieee.org
In the above-named work, we proposed a novel framework that uses a constrained
formulation of sum of squared correlation (SSCOR) approach as an alternative method for …
formulation of sum of squared correlation (SSCOR) approach as an alternative method for …
A benchmarking framework for improving machine learning with fNIRS neuroimaging data
J Benerradi - 2023 - eprints.nottingham.ac.uk
Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging technology
that presents attractive advantages such as a good compromise between temporal …
that presents attractive advantages such as a good compromise between temporal …
[HTML][HTML] Benchmarking framework for machine learning classification from fNIRS data
Background While efforts to establish best practices with functional near infrared
spectroscopy (fNIRS) signal processing have been published, there are still no community …
spectroscopy (fNIRS) signal processing have been published, there are still no community …
Benchmarking framework for machine learning classification from fNIRS data
Background While efforts to establish best practices with functional near infrared
spectroscopy (fNIRS) signal processing have been published, there are still no community …
spectroscopy (fNIRS) signal processing have been published, there are still no community …
Research on SSVEPs in Correlational Convolutional Neural Networks Based on Filter Banks
D Han, Y Dong, X Wen, C Gao, R Cao, Y Guo, J Xiang - papers.ssrn.com
Currently, in the field of steady-state visual evoked potential brain computer interfaces
(SSVEPs-BCIs) research, convolutional neural networks (CNNs) have gradually been …
(SSVEPs-BCIs) research, convolutional neural networks (CNNs) have gradually been …