200 Open source projects that are alternatives of or similar to eeg-gcnn

Open-Source board for converting RaspberryPI to Brain-computer interface

EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow

A convolutional neural network developed in python using the Keras machine learning framework used to categorize brain signal based on what a user was looking at when the EEG data was collected.

[IEEE TNSRE] "An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG"

Implement of DiGCN, NeurIPS-2020

With the Brain Powered honourscourse at the UvA we aimed to control a drone using brain signals, measured by means of EEG, only.

Motor Imagery EEG Signal Classification Using Random Subspace Ensemble Network

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

A package for manipulating EEG data in R.

Empirical wavelet transform (EWT) in Python

Pytorch differentiable molecular dynamics

Awesome Graph Self-Supervised Learning

🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba 来自阿里巴巴的一站式大规模图计算系统 图分析 图查询 图机器学习

The Human Neocortical Neurosolver (HNN) is a software tool that gives researchers/clinicians the ability to develop/test hypotheses on circuit mechanisms underlying EEG/MEG data.

source code for signed graph attention networks (ICANN2019) & SDGNN (AAAI2021)

Official code for NeurRIPS 2020 paper "Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3D"

Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch

Code snippets and solutions for the Introduction to Deep Learning and Neural Networks Course hosted in educative.io

Source Code for "Adaptive Transfer Learning with Deep CNN for EEG Motor Imagery Classification".

AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

MSc thesis on: Classifying brain activity using EEG and automated time tracking of computer use (using ActivityWatch)

Probabilistic Type Inference using Graph Neural Networks

Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)

Tutorials for Machine Learning on Graphs

Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".

Summary of social recommendation papers and codes

Variational mode decomposition (VMD) in Python

Locally Private Graph Neural Networks (ACM CCS 2021)

A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).

Meta-Learning through Hebbian Plasticity in Random Networks: https://arxiv.org/abs/2007.02686

PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)

A terminal app written in Node.js to monitor brain signals in real-time

Simulation and optimization of neural circuits for MEG/EEG source estimates

Official implementation of Neural Bellman-Ford Networks (NeurIPS 2021)

A spherical CNN for weather forecasting

Code for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)

Codes for NeurIPS 2020 paper "Adversarial Weight Perturbation Helps Robust Generalization"

Code of the NeurIPS 2021 paper: Language and Visual Entity Relationship Graph for Agent Navigation

Subgraph Neural Networks (NeurIPS 2020)

Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)

Open Source EIT system using Keithley 6221 current source and EEG systems

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022

Repo for "3D-PV-Locator: Large-scale detection of rooftop-mounted photovoltaic systems in 3D" based on Applied Energy publication.

Code to accompany our International Joint Conference on Neural Networks (IJCNN) paper entitled - Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification

A C++ package for low-frequency bio-electromagnetism solving forward problems in the field of EEG and MEG.

The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021

[ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision

Official implementation of CATs

Context-Aware Visual Compatibility Prediction (https://arxiv.org/abs/1902.03646)

PyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"

Graph-based machine learning for chemical property prediction

🔧🧠 MEEGkit: MEG & EEG processing toolkit in Python 🧠🔧

Reimplementation of Graph Embedding methods by Pytorch.

Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"

Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning (authors' MXNet implementation for the TACL19 paper)

EEG Reader is an Android mobile application, which reads EEG signal from NeuroSky mobile device connected to smartphone via Bluetooth.

Code and data for ECML-PKDD paper "Social Influence Attentive Neural Network for Friend-Enhanced Recommendation"

Message Passing Neural Networks for Simplicial and Cell Complexes

An index of recommendation algorithms that are based on Graph Neural Networks.

Connectome Mapper 3 is a BIDS App that implements full anatomical, diffusion, resting/state functional MRI, and recently EEG processing pipelines, from raw T1 / DWI / BOLD , and preprocessed EEG data to multi-resolution brain parcellation with corresponding connection matrices.