A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification | Paper Citation Record

Observation b98c6e2c-4ad7-49fe-8222-a7b7f8429d7f · outbound

This paper cites Parkinson's disease diagnosis using deep learning: A bibliometric analysis and literature review.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Parkinson's disease diagnosis using deep learning: A bibliometric analysis and literature review

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A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Unresolved cited work

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This paper cites Predictive accuracy of CNN for cortical oscillatory activity in an acute rat model of parkinsonism.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Predictive accuracy of CNN for cortical oscillatory activity in an acute rat model of parkinsonism

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This paper cites Invariant Risk Minimization.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Invariant Risk Minimization

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This paper cites Deep brain stimulation of the subthalamic nucleus for the treatment of Parkinson's disease.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Deep brain stimulation of the subthalamic nucleus for the treatment of Parkinson's disease

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This paper cites A riemannian modification of artifact subspace reconstruction for EEG artifact handling.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification A riemannian modification of artifact subspace reconstruction for EEG artifact handling

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This paper cites Prediction of mild Parkinsonism revealed by neural oscillatory changes and machine learning.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Prediction of mild Parkinsonism revealed by neural oscillatory changes and machine learning

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This paper cites Deep Learning-Driven EEG Analysis for Personalized Deep Brain Stimulation Programming in Parkinson's Disease.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Deep Learning-Driven EEG Analysis for Personalized Deep Brain Stimulation Programming in Parkinson's Disease

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Observation 627fca83-8ccd-4c7f-8156-affc00b29485 · outbound

This paper cites A method for optimizing the artifact subspace reconstruction performance in low-density EEG.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification A method for optimizing the artifact subspace reconstruction performance in low-density EEG

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This paper cites Diminished EEG habituation to novel events effectively classifies Parkinson's patients.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Diminished EEG habituation to novel events effectively classifies Parkinson's patients

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This paper cites Evaluation of artifact subspace reconstruction for automatic EEG artifact removal.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Evaluation of artifact subspace reconstruction for automatic EEG artifact removal

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This paper cites Transformer-based neural speech decoding from surface and depth electrode signals.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Transformer-based neural speech decoding from surface and depth electrode signals

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This paper cites Kernel two-sample tests for manifold data.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Kernel two-sample tests for manifold data

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Observation 9e5c9ab6-5ee2-48a3-8576-db34f0edfd67 · outbound

This paper cites Cluster embedding joint-probability-discrepancy transfer for cross-subject seizure detection.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Cluster embedding joint-probability-discrepancy transfer for cross-subject seizure detection

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

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Towards best practice of interpreting deep learning models for EEG-based brain computer interfaces

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This paper cites MADG: margin-based adversarial learning for domain generalization.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification MADG: margin-based adversarial learning for domain generalization

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This paper cites Disentangling document topic and author gender in multiple languages: Lessons for adversarial debiasing.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Disentangling document topic and author gender in multiple languages: Lessons for adversarial debiasing

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This paper cites Global, regional, and national burden of Parkinson's disease, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Global, regional, and national burden of Parkinson's disease, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

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Observation 64bb7a5a-acd0-409c-8ca2-7c72f1282c56 · outbound

This paper cites Variational mode decomposition.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Variational mode decomposition

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This paper cites Domain-adversarial training of neural networks.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Domain-adversarial training of neural networks

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This paper cites Elucidating relations between fMRI, ECoG, and EEG through a common natural stimulus.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Elucidating relations between fMRI, ECoG, and EEG through a common natural stimulus

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This paper cites The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, In: Proceedings of the Royal Society of London.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, In: Proceedings of the Royal Society of London

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This paper cites Discrepancy between inter- and intra-subject variability in EEG-based motor imagery brain-computer interface: Evidence from multiple perspectives.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Discrepancy between inter- and intra-subject variability in EEG-based motor imagery brain-computer interface: Evidence from multiple perspectives

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Observation 65594429-3a74-4ff9-856a-acef58d8ceb5 · outbound

This paper cites M., Hersche, M., Wang, X., Kobayashi, N., Cavigelli, L., et al., 2020.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification M., Hersche, M., Wang, X., Kobayashi, N., Cavigelli, L., et al., 2020

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This paper cites Do, Song, I.U., Chung, Y.A., Jeong, J., 2016.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Do, Song, I.U., Chung, Y.A., Jeong, J., 2016

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This paper cites Bi-Band ECoGNet for ECoG Decoding on Classification Task.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Bi-Band ECoGNet for ECoG Decoding on Classification Task

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This paper cites Parkinson's disease.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Parkinson's disease

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This paper cites Unsupervised domain adaptation in brain lesion segmentation with adversarial networks.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Unsupervised domain adaptation in brain lesion segmentation with adversarial networks

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A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Data augmentation with suboptimal warping for time-series classification

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This paper cites Electrocorticogram (ECOG) is highly informative in primate visual cortex.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Electrocorticogram (ECOG) is highly informative in primate visual cortex

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This paper cites Distinguishing Parkinson's disease with GLCM features from the hankelization of EEG signals.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Distinguishing Parkinson's disease with GLCM features from the hankelization of EEG signals

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A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification The influence of filters on EEG-ERP testing: Analysis of motor cortex in healthy subjects

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A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Learning not to learn: Training deep neural networks with biased data

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A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Explainable AI-Driven Neural Activity Analysis in Parkinsonian Rats under Electrical Stimulation

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A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Efficient artifact removal from low-density wearable EEG using artifacts subspace reconstruction

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A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Unsupervised representation learning visualization for brain activity dynamics in REM-sleep

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A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification High-frequency neural activity and human cognition: Past, present and possible future of intracranial EEG research

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A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Self-supervised learning for seizure classification using ECoG spectrograms

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A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification EEGNet: A compact convolutional neural network for EEG-based brain-computer interfaces

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A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Domain generalization with adversarial feature learning

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A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Adaptive deep brain stimulation in advanced Parkinson disease

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Observation d5348ffa-bc28-4808-8fac-d6c1ca8f00e2 · outbound

This paper cites Reducing the subject variability of eeg signals with adversarial domain generalization, In: International Conference on Neural Information Processing.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Reducing the subject variability of eeg signals with adversarial domain generalization, In: International Conference on Neural Information Processing

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A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Independent component analysis of electroencephalographic data

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A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Conserved structures of neural activity in sensorimotor cortex of freely moving rats allow cross-subject decoding

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This paper cites RISE-iEEG: Robust to Inter-Subject Electrodes Implantation Variability iEEG Classifier.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification RISE-iEEG: Robust to Inter-Subject Electrodes Implantation Variability iEEG Classifier

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This paper cites Cortical activity during motor execution, motor imagery, and imagery-based online feedback.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Cortical activity during motor execution, motor imagery, and imagery-based online feedback

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This paper cites Domain generalization via invariant feature representation.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Domain generalization via invariant feature representation

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

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Real-time neuroimaging and cognitive monitoring using wearable dry EEG

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This paper cites Parkinson's disease detection from resting state EEG using multi-head graph structure learning with gradient weighted graph attention explanations.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Parkinson's disease detection from resting state EEG using multi-head graph structure learning with gradient weighted graph attention explanations

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This paper cites FASTER: fully automated statistical thresholding for EEG artifact rejection.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification FASTER: fully automated statistical thresholding for EEG artifact rejection

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This paper cites A novel automated Parkinson's disease identification approach using deep learning and EEG.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification A novel automated Parkinson's disease identification approach using deep learning and EEG

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This paper cites Past, present, and future of Parkinson's disease: A special essay on the 200th Anniversary of the Shaking Palsy.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Past, present, and future of Parkinson's disease: A special essay on the 200th Anniversary of the Shaking Palsy

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Observation 951c3ed3-3e42-486d-8b16-36b4784a30ac · outbound

This paper cites A deep learning approach for Parkinson's disease diagnosis from EEG signals.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification A deep learning approach for Parkinson's disease diagnosis from EEG signals

Reference 53

Resolution: verified exact; doi, observed 2026-08-03T01:13:25.927447Z

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Observation 41693e17-58fe-4dc3-bb38-98bad02b6c7f · outbound

This paper cites AMICA: An adaptive mixture of independent component analyzers with shared components.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification AMICA: An adaptive mixture of independent component analyzers with shared components

Reference 54

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Observation ae02a785-f985-43fc-8258-ab9e1ee839a5 · outbound

This paper cites On the high dimensional power of a linear-time two sample test under mean-shift alternatives.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification On the high dimensional power of a linear-time two sample test under mean-shift alternatives

Reference 55

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Observation bc86e15e-811a-40ed-b734-c1b73aad0d55 · outbound

This paper cites CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-08-03T01:13:25.813922Z

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This paper cites Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization

Reference 57

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This paper cites Single-trial EEG analysis using an adaptive autoregressive model.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Single-trial EEG analysis using an adaptive autoregressive model

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-03T01:08:47.055180Z

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Observation f2ad3104-c58d-4684-b068-42d5ce9dcb09 · outbound

This paper cites Dynamical system based compact deep hybrid network for classification of Parkinson disease related EEG signals.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Dynamical system based compact deep hybrid network for classification of Parkinson disease related EEG signals

Reference 59

Resolution: verified exact; doi, observed 2026-08-03T01:13:25.638774Z

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Observation 5dd4c092-9960-41a0-af8d-d2a345b69934 · outbound

This paper cites Generalizing Across Domains via Cross-Gradient Training.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Generalizing Across Domains via Cross-Gradient Training

Reference 60

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Observation 39f83b1a-00c1-44b4-89ac-9cf1abd2c298 · outbound

This paper cites A Wireless Cortical Surface Implant for Diagnosing and Alleviating Parkinson's Disease Symptoms in Freely Moving Animals.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification A Wireless Cortical Surface Implant for Diagnosing and Alleviating Parkinson's Disease Symptoms in Freely Moving Animals

Reference 61

Resolution: verified exact; doi, observed 2026-08-03T01:13:25.478837Z

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Observation cf45b285-041a-4ad0-9e9c-98b6126f113d · outbound

This paper cites Frontal theta and beta oscillations during lower-limb movement in Parkinson's disease.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Frontal theta and beta oscillations during lower-limb movement in Parkinson's disease

Reference 62

Resolution: verified exact; doi, observed 2026-08-03T01:13:25.357874Z

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Observation 98d222dd-e2c3-4c69-8a2c-43ef6b7bd9f2 · outbound

This paper cites Dusk2Dawn: an EEGLAB plugin for automatic cleaning of whole-night sleep electroencephalogram using Artifact Subspace Reconstruction.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Dusk2Dawn: an EEGLAB plugin for automatic cleaning of whole-night sleep electroencephalogram using Artifact Subspace Reconstruction

Reference 63

Resolution: verified exact; doi, observed 2026-08-03T01:13:25.182225Z

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Observation 991afb82-333f-43a1-9a76-e37756e679d2 · outbound

This paper cites EEG conformer: Convolutional transformer for EEG decoding and visualization.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification EEG conformer: Convolutional transformer for EEG decoding and visualization

Reference 64

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This paper cites EEG and MEG coherence: Measures of functional connectivity at distinct spatial scales of neocortical dynamics.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification EEG and MEG coherence: Measures of functional connectivity at distinct spatial scales of neocortical dynamics

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-03T01:08:47.869711Z

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Observation e849d484-1ef8-44c1-baca-1db89d639d72 · outbound

This paper cites Generalizable electroencephalographic classification of Parkinson's disease using deep learning.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Generalizable electroencephalographic classification of Parkinson's disease using deep learning

Reference 66

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This paper cites Local domain generalization with low-rank constraint for EEG-based emotion recognition.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Local domain generalization with low-rank constraint for EEG-based emotion recognition

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-03T01:08:48.103115Z

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This paper cites Intracranial EEG fluctuates over months after implanting electrodes in human brain.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Intracranial EEG fluctuates over months after implanting electrodes in human brain

Reference 68

Resolution: verified exact; doi, observed 2026-08-03T01:13:24.993443Z

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Observation 4389c2e5-5cce-4b02-a27f-2c08e18c8294 · outbound

This paper cites A longitudinal electrophysiological and behavior dataset for PD rat in response to deep brain stimulation.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification A longitudinal electrophysiological and behavior dataset for PD rat in response to deep brain stimulation

Reference 69

Resolution: verified exact; doi, observed 2026-08-03T01:13:24.850545Z

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Observation c1b4b6f1-c1f7-4d0e-8e60-d5df9ab043ac · outbound

This paper cites DMMR: Cross-subject domain generalization for EEG-based emotion recognition via denoising mixed mutual reconstruction.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification DMMR: Cross-subject domain generalization for EEG-based emotion recognition via denoising mixed mutual reconstruction

Reference 70

Resolution: verified exact; doi, observed 2026-08-03T01:13:24.742073Z

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Observation ca92326d-fee7-4d8a-ac9f-7bba1c8c31c2 · outbound

This paper cites Bilateral deep brain stimulation vs best medical therapy for patients with advanced parkinson disease: A randomized controlled trial.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Bilateral deep brain stimulation vs best medical therapy for patients with advanced parkinson disease: A randomized controlled trial

Reference 71

Resolution: verified exact; doi, observed 2026-08-03T01:13:24.646269Z

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Observation c3068155-5882-46b3-9eeb-c15e596059eb · outbound

This paper cites Adversarial Training based Domain Adaptation for Cross-Subject Emotion Recognition.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Adversarial Training based Domain Adaptation for Cross-Subject Emotion Recognition

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-03T01:08:48.672534Z

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Observation 21c8da24-1df6-4f26-a839-2b9f8362904a · outbound

This paper cites Towards Stable and Comprehensive Domain Alignment: Max-Margin Domain-Adversarial Training.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Towards Stable and Comprehensive Domain Alignment: Max-Margin Domain-Adversarial Training

Reference 73

Resolution: verified exact; local_arxiv, observed 2026-08-03T01:13:24.527149Z

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Observation 2250393e-8ac0-4c75-b6e0-bdf6ea167ed3 · outbound

This paper cites Impact of dataset size and long-term ECoG-based BCI usage on deep learning decoders performance.

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification Impact of dataset size and long-term ECoG-based BCI usage on deep learning decoders performance

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-03T01:08:48.814023Z

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