The Cross-modal SleepTransformer is a deep learning model designed for sleep stage classification based on multimodal physiological signals. It utilizes the transformer architecture, and cross-atte…

Official implementation of "MARS, Multi-Agent Reinforcement Learning for Spatial-Spectral and Temporal Feature Selection in EEG-based BCI"

EEG prediction using Chaos Theory, Dynamical Systems Theory, and neural networks

A modular active learning framework for Python

joint sample and feature importance assessment

NeurIPS2023 - A generic biosignal learning framework. Large EEG pre-trained models.

META-EEG: Meta-learning-based Class-relevant EEG Representation Learning for Zero-calibration Brain-computer Interfaces

Neural network classifier for MELD

TorchEEG is a library built on PyTorch for EEG signal analysis.

Exploration on introducing discrete codex and raw wave decoding to realize Brain-to-Text translation.

Officially Accepted to IEEE Transactions on Medical Imaging (TMI, IF: 11.037) - Special Issue on Geometric Deep Learning in Medical Imaging.

About Open source code of paper: Toward reliable signals decoding for electroencephalogram: A benchmark study to EEGNeX

Accompanying code repository for NEMO, A Database for Emotion Analysis Using Functional Near-infrared Spectroscopy

[TNNLS-2023] This is the PyTorch implementation of LGGNet.

A Python package for handling and visualizing GWAS summary statistics. https://cloufield.github.io/gwaslab/

Survival analysis with PyTorch

MRI-based quantitative measure of intra-tumoral heterogeneity in breast cancer

This is an implentation of paper “MTL-MGAWS: Multi-Task Learning Combining Masked Graph Autoencoder and Weight Sharing for EEG Emotion Recognition”

Matlab code for SBLEST algorithm

This repository contains the code for our proposed method "Multi-source Feature Alignment and Label Rectification" (MFA-LR), which has been published in the paper "Learning a Robust Unified Domain …

Code to reproduce figures in "Interrater Reliability of Expert Electroencephalographers Identifying Seizures and Rhythmic and Periodic Patterns in EEGs"

Resources for the paper titled "Domain-guided Self-supervision of EEG Data Improves Downstream Classification Performance and Generalizability". Accepted at ML4H Symposium 2021 with an oral spotlight!

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cycleg…