Pedro L. C. Rodrigues

RPA. Python code for the Riemannian Procrustes Analysis (RPA) method

py.ALPHA.EEG.2017-GIPSA. Codes for working with the "EEG Alpha Waves Dataset" developed at the GIPSA-lab

Workshop-MOABB-BCI-Graz-2019. This is the repository with the materials for the Graz BCI 2019 workshop : "Benchmarking BCI classification methods: a hands-on introduction"

HNPE. Repository with the code of "HNPE: Leveraging Global Parameters for Neural Posterior Estimation"

py.VR.EEG.2018-GIPSA. Codes for working with the "EEG-based BCI experiment in Virtual Reality and on a Personal Computer" dataset developed at the GIPSA-lab

py.BI.EEG.2013-GIPSA. Code for working with EEG recordings of a visual P300 Brain-Computer Interface

PhD-Code. This repository contains scripts for reproducing some of the examples in my Ph.D. manuscript

py.BI.EEG.2015b-GIPSA. Code for working with EEG recordings of a visual P300 Brain-Computer Interface

py.BI.EEG.2014a-GIPSA. Code for working with EEG recordings of a visual P300 Brain-Computer Interface

py.BI.EEG.2015a-GIPSA. Code for working with EEG recordings of a visual P300 Brain-Computer Interface

means-field-classifier. Repository for the paper "The Riemannian Minimum Distance to Means Field Classifier"

py.BI.EEG.2012-GIPSA. Code for working with EEG recordings of a visual P300 Brain-Computer Interface

py.PHMDML.EEG.2017-GIPSA. Codes for working with the "Passive Head-Mounted Display Music-Listening EEG" developed at the GIPSA-lab

TVPDC. MATLAB

py.BI.EEG.2014b-GIPSA. Code for working with EEG recordings of a visual P300 Brain-Computer Interface

DT. Code for our IEEE TBME 2020 paper on Dimensionality Transcending

GrazBCI2019-PowerMeans. Python