Pinned Repositories
Awesome-Graph-Neural-Networks
Paper Lists for Graph Neural Networks
CapsGNN
A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).
CM-graph
The Python Toolbox for multichannel EEG-EMG connectivity analysis. This package is an extention of mne-tool with the focus on the application of the newest graph and network theory. It is first developped to investigate stroke and autism spectral disorder(ASD) via EEG-EMG coherence marker
EEG-Motor-Imagery-Classification-CNNs-TensorFlow
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
GNNPapers
Must-read papers on graph neural networks (GNN)
Neural-Networks-for-time-series-analysis
Compare how ANNs, RNNs, LSTMs, and LSTMs with attention perform on time-series analysis
pytorch_geometric
Graph Neural Network Library for PyTorch
arl-eegmodels
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
BCI-2021-Riemannian-Geometry-workshop
Riemannian Geometry workshop at vBCI Meeting 2021
BCI_MI_Wavelet_CNN
Using wavelet transform to extract time-frequency features of motor imagery EEG signals, and classify it by convolutional neural network
nataliamolano's Repositories
nataliamolano/geometric-gnn-dojo
Geometric GNN Dojo provides unified implementations and experiments to explore the design space of Geometric Graph Neural Networks.
nataliamolano/pytorch_geometric
Graph Neural Network Library for PyTorch
nataliamolano/mne-python
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
nataliamolano/eeg-notebooks
J
nataliamolano/Deep-Learning-for-BCI
Resources for Book: Deep Learning for EEG-based Brain-Computer Interface: Representations, Algorithms and Applications
nataliamolano/tools
nataliamolano/PySimMIBCI
Codes for employing PySimMIBCI for MI-EEG data generation and for using such data with FBCNetToolbox models
nataliamolano/EEG-Motor-Imagery-Classification-CNNs-TensorFlow
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
nataliamolano/EEG-DL
A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.
nataliamolano/GNNPapers
Must-read papers on graph neural networks (GNN)
nataliamolano/medusa-kernel
nataliamolano/DeepEEG
Deep Learning with Tensor Flow for EEG MNE Epoch Objects
nataliamolano/Python-Emotion-using-EEG-Signal
This repository contains the code for emotion recognition using wavelet transform and svm classifiers' rbf kernel.
nataliamolano/CapsGNN
A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).
nataliamolano/benchmarking-gnns
Repository for benchmarking graph neural networks
nataliamolano/CM-graph
The Python Toolbox for multichannel EEG-EMG connectivity analysis. This package is an extention of mne-tool with the focus on the application of the newest graph and network theory. It is first developped to investigate stroke and autism spectral disorder(ASD) via EEG-EMG coherence marker
nataliamolano/Awesome-Graph-Neural-Networks
Paper Lists for Graph Neural Networks
nataliamolano/eeg-pipeline
End-to-End EEG Pipeline for cleaning, filtering, ICA, mass-univariate, and decoding analysis using MNE python
nataliamolano/arl-eegmodels
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
nataliamolano/Winter2022class
nataliamolano/cuadrados-medios
Generación de números pseudoaleatorios implementando el método de cuadrados medios
nataliamolano/Biomedical_Filter_Design
Using the MATLAB filter designer, we created IIR and FIR filters for both EEG and VGRF signals
nataliamolano/pyeeg
Python + EEG/MEG = PyEEG
nataliamolano/ChebLieNet
ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.
nataliamolano/BCI-2021-Riemannian-Geometry-workshop
Riemannian Geometry workshop at vBCI Meeting 2021
nataliamolano/powerful-gnns
How Powerful are Graph Neural Networks?
nataliamolano/nsp-course
Python implementations for the "Complete neural signal processing and analysis: Zero to hero" course
nataliamolano/genbci
[Work in progress] A library for EEG BCI data simulation.
nataliamolano/BCI_MI_Wavelet_CNN
Using wavelet transform to extract time-frequency features of motor imagery EEG signals, and classify it by convolutional neural network
nataliamolano/mushu
BCI signal acquisition