drzohaibh Goto Github PK

brainflow

BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors

challenge-iclr-2022

GitHub repository for the ICLR Computational Geometry & Topology Challenge 2022

dbm-transient

DBM-Transient: A MATLAB implementation of a Deep Boltzmann Machine (DBM) in to a new transient state.

dimensionality_reduction_alo_codes

特征提取/数据降维:PCA、LDA、MDS、LLE、TSNE等降维算法的python实现

dreem-learning-evaluation

Code to reproduce results from the paper "Dreem Open Datasets: Multi-Scored Sleep Datasets to compare Human and Automated sleep staging"

ecephys

Python extracellular electrophysiology tools

electronics2023

geomstats

Computations and statistics on manifolds with geometric structures.

intrinsic-manifolds

Code used for paper: Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep. Rué-Queralt et al. Communications Biology (2021)

kpca-matlab

MATLAB code for dimensionality reduction, feature extraction, fault detection, and fault diagnosis using Kernel Principal Component Analysis (KPCA).

lpproj

Locality Preserving Projections in Python

megaman

megaman: Manifold Learning for Millions of Points

ml-dl_book

Machine learning, Deep learning

npe-and-lpp

Supervised Neighborhood Preserving Embedding and Locality Presering Projections（LPP）in python

npnn

Neighborhood Preserving Neural Network

python_for_microscopists

Working

sbea_release

The release version of Social Behavior Atlas (SBeA)

simba

SimBA (Simple Behavioral Analysis), a pipeline and GUI for developing supervised behavioral classifiers

sklearn-lpp

scikit-learn implementation of locality preserving projections (LPP)

sklearn_tutorial

Scikit-learn tutorial

sleep-datasets

Sleep datasets obtained using PSG for automatic sleep stage scoring.

sleepeegpy

svdd-python

Python code for abnormal detection using Support Vector Data Description (SVDD)

weak-disentanglement

Code of the "Leveraging Relational Information for Learning Weakly Disentangled Representations" paper.