Stars
Official codebase of EEG-JEPA: Structured Latent Prediction for EEG Foundation Models
Training and evaluation pipeline for MEG and EEG brain signal encoding and decoding using deep learning. Code for our paper "Decoding speech perception from non-invasive brain recordings" published…
Fair and comprehensive benchmarking for open source EEG foundation models.
EEG-DaSh: an open data, tool, and compute resource. a Python library and catalog for 700+ BIDS-first EEG, MEG, fNIRS, EMG, and iEEG datasets, ML-ready via PyTorch
Python implementation of Empirical Mode Decompoisition (EMD) method
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
[ICLR 2024 spotlight] Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI
[ICLR 2025] CBraMod: A Criss-Cross Brain Foundation Model for EEG Decoding
[ICLR 2024] M/EEG-based image decoding with contrastive learning. i. Propose a contrastive learning framework to align image and eeg. ii. Resolving brain activity for biological plausibility.
Exercises for "Neuroscience for machine learners" course
Draw datasets from within Python notebooks.
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
a public domain dataset of EEG recordings for music imagery information retrieval
Code and hyperparameters for the paper "Generative Adversarial Networks"
Implement Generative Adversarial Nets by Tensorflow