MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

This page contains Python codes for the chapters appearing in all 3 volumes of the work "Sayed, Ali. H., Inference and Learning from Data, vols. 1-3, Cambridge University Press, 2022". Matlab codes…

Graph Signal Processing in Python

An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).

This project extends the idea of the innovative architecture of Kolmogorov-Arnold Networks (KAN) to the Convolutional Layers, changing the classic linear transformation of the convolution to learna…

Fast CUDA implementation of (differentiable) soft dynamic time warping for PyTorch

Explain model and feature dependencies by decomposition of SHAP values

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

Kolmogorov Arnold Networks

This is a trial implementation of EEGNet with KANs. Repository is under construction.

Deep learning software to decode EEG, ECG or MEG signals

A list of examples for Machine Learning: Transformers, Large Language Models, Keras for Deep Learning, Transfer Learning with PyTorch for Image Classification, EEG Classification, Decision Trees, S…

Mother of All BCI Benchmarks

Constrained optimization toolkit for PyTorch

The implementation of FedBCD algorithm published in the paper "FedBCD: A Communication-Efficient Collaborative Learning Framework for Distributed Features"

Efficient Riemannian Optimization on Stiefel Manifold via Cayley Transform

selfEEG: a Python library for Self-Supervised Learning on Electroencephalography (EEG) data