403 papers with code • 0 benchmarks • 1 datasets



Use these libraries to find EEG models and implementations


Most implemented papers

SGDR: Stochastic Gradient Descent with Warm Restarts

loshchil/SGDR 13 Aug 2016

Partial warm restarts are also gaining popularity in gradient-based optimization to improve the rate of convergence in accelerated gradient schemes to deal with ill-conditioned functions.

Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks

pbashivan/EEGLearn 19 Nov 2015

One of the challenges in modeling cognitive events from electroencephalogram (EEG) data is finding representations that are invariant to inter- and intra-subject differences, as well as to inherent noise associated with such data.

EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces

vlawhern/arl-eegmodels 23 Nov 2016

We introduce the use of depthwise and separable convolutions to construct an EEG-specific model which encapsulates well-known EEG feature extraction concepts for BCI.

DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

akaraspt/deepsleepnet 12 Mar 2017

This demonstrated that, without changing the model architecture and the training algorithm, our model could automatically learn features for sleep stage scoring from different raw single-channel EEGs from different datasets without utilizing any hand-engineered features.

Deep learning with convolutional neural networks for EEG decoding and visualization

braindecode/braindecode 15 Mar 2017

PLEASE READ AND CITE THE REVISED VERSION at Human Brain Mapping: http://onlinelibrary. wiley. com/doi/10. 1002/hbm. 23730/full Code available here: https://github. com/robintibor/braindecode

U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging

perslev/U-Time NeurIPS 2019

We propose U-Time, a fully feed-forward deep learning approach to physiological time series segmentation developed for the analysis of sleep data.

An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

pulp-platform/pulp 18 Dec 2016

Near-sensor data analytics is a promising direction for IoT endpoints, as it minimizes energy spent on communication and reduces network load - but it also poses security concerns, as valuable data is stored or sent over the network at various stages of the analytics pipeline.

Comparative evaluation of state-of-the-art algorithms for SSVEP-based BCIs

MAMEM/ssvep-eeg-processing-toolbox 2 Feb 2016

Brain-computer interfaces (BCIs) have been gaining momentum in making human-computer interaction more natural, especially for people with neuro-muscular disabilities.

Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise

sweichwald/coroICA-python 4 Jun 2018

We introduce coroICA, confounding-robust independent component analysis, a novel ICA algorithm which decomposes linearly mixed multivariate observations into independent components that are corrupted (and rendered dependent) by hidden group-wise stationary confounding.

Deep learning-based electroencephalography analysis: a systematic review

kylemath/DeepEEG 16 Jan 2019

To help the field progress, we provide a list of recommendations for future studies and we make our summary table of DL and EEG papers available and invite the community to contribute.