Improving EEG Classification Through Randomly Reassembling Original and
Generated Data with Transformer-based Diffusion Models

Improving EEG Classification Through Randomly Reassembling Original and Generated Data with Transformer-based Diffusion Models

20 July 2024

Papers citing "Improving EEG Classification Through Randomly Reassembling Original and Generated Data with Transformer-based Diffusion Models"

11 / 11 papers shown

Title
Do Generated Data Always Help Contrastive Learning? Yifei Wang Jizhe Zhang Yisen Wang DiffM 57 23 0 19 Mar 2024
Enhancing EEG Signal-Based Emotion Recognition with Synthetic Data: Diffusion Model Approach Gourav Siddhad Masakazu Iwamura Partha Pratim Roy DiffM 42 7 0 30 Jan 2024
Classifier-Free Diffusion Guidance Jonathan Ho Tim Salimans FaML 133 3,830 0 26 Jul 2022
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness Francesco Pinto Harry Yang Ser-Nam Lim Philip Torr P. Dokania UQCV 70 35 0 29 Jun 2022
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 205 30,069 0 01 Mar 2022
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features Sangdoo Yun Dongyoon Han Seong Joon Oh Sanghyuk Chun Junsuk Choe Y. Yoo OOD 595 4,735 0 13 May 2019
CBAM: Convolutional Block Attention Module Sanghyun Woo Jongchan Park Joon-Young Lee In So Kweon 191 16,337 0 17 Jul 2018
EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signals K. Hartmann R. Schirrmeister T. Ball GAN AI4TS 48 231 0 05 Jun 2018
Neural Discrete Representation Learning Aaron van den Oord Oriol Vinyals Koray Kavukcuoglu BDL SSL OCL 192 4,928 0 02 Nov 2017
EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces Vernon J. Lawhern Amelia J. Solon Nicholas R. Waytowich Stephen M. Gordon C. Hung Brent Lance OOD 86 2,855 0 23 Nov 2016
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 397 16,962 0 20 Dec 2013