lucas-heck's Stars
GitWR/U-SPDNet
This work has been accepted by Neural Networks.
GitWR/DreamNet
This is a matlab implementation of our article, titled "DreamNet: A Deep Riemannian Manifold Network for SPD Matrix Learning", which has recently been accepted by the 16th Asian Conference on Computer Vision (ACCV2022).
GeometricBCI/Tensor-CSPNet-and-Graph-CSPNet
This is the python implementation of Tensor-CSPNet and Graph-CSPNet.
pymanopt/pymanopt
Python toolbox for optimization on Riemannian manifolds with support for automatic differentiation
mccorsi/FUCONE
woozch/DSBN
Official Implementation of "Domain Specific Batch Normalization for Unsupervised Domain Adaptation (CVPR2019)"
YirongMao/SPDNet
This is an unofficial PyTorch implementation for paper "A Riemannian Network for SPD Matrix Learning", AAAI 2017
LLNL/spdlayers
Symmetric Positive Definite (SPD) layers for PyTorch
xl0/lovely-tensors
Tensors, for human consumption
rkobler/TSMNet
Code and reuslts accompanying the NeurIPS 2022 paper with the title SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG
hubertjb/dl-eeg-review
Supplementary material for systematic literature review on deep learning and EEG.
penrose/penrose
Create beautiful diagrams just by typing notation in plain text.
gzoumpourlis/BEETL_NeurIPS_2021
Submission to the Motor Imagery track of BEETL competition, organized within NeurIPS 2021
xuhuisheng/rocm-build
build scripts for ROCm
pikawika/VUB-BCI-thesis
GitHub repository of BCI related Master Thesis @ VUB 2021-2022
zhiwu-huang/SPDNet
GitHub repository for "A Riemannian Network for SPD Matrix Learning", AAAI 2017.
ErikBjare/thesis
MSc thesis on: Classifying brain activity using EEG and automated time tracking of computer use (using ActivityWatch)
mcd4874/NeurIPS_competition
code for NeurIPS_competition
ziyujia/Physiological-Signal-Classification-Papers
A list of papers for physiological signal classification using machine learning/deep learning.
xuhuisheng/rocm-gfx803
adavoudi/spdnet
Implementation of Deep SPDNet in pytorch
eeyhsong/EEG-Transformer
i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension (channel attention) and *temporal dimension*. iii. Common spatial pattern (CSP), an efficient feature enhancement method, realized with Python.
Serpeve/EEGSym
Open implementation and code from the publication "EEGSym: Overcoming Intersubject Variability in Motor Imagery Based BCIs with Deep Learning"
neurreps/awesome-neural-geometry
A curated collection of resources and research related to the geometry of representations in the brain, deep networks, and beyond
CYHSM/awesome-neuro-ai-papers
Papers from the intersection of deep learning and neuroscience
PoE-TradeMacro/POE-TradeMacro
Price checking script for Path of Exile.
cuijiancorbin/Towards-Best-Practice-of-Interpreting-Deep-Learning-Models-for-EEG-based-BCI
In this project, we implemented 7 interpretation techniques on two benchmark deep learning models "EEGNet" and "InterpretableCNN" for EEG-based BCI. The methods include: gradientĂ—input, DeepLIFT, integrated gradient, layer-wise relevance propagation (LRP), saliency map, deconvolution, and guided backpropagation
comojin1994/m-shallowconvnet
Rethinking CNN Architecture for Enhancing Decoding Performance of Motor Imagery-based EEG Signals
realblack0/MI_classification_paper
Fuminides/athena
Athena is a library that comprises many different bci frameworks that perform classification on a set of eeg data.