A new algorithm for neural connectivity estimation of EEG event related potentials. - Pedro L. C. Rodrigues; Luiz A. Baccalá (EMBC, 2015)

Statistically significant time-varying neural connectivity estimation using generalized partial directed coherence. - Pedro L. C. Rodrigues; Luiz A. Baccalá (EMBC, 2016)

A closed-form unsupervised geometry-aware dimensionality reduction method in the Riemannian Manifold of SPD matrices. - Marco Congedo; Pedro Luiz Coelho Rodrigues; Florent Bouchard; Alexandre Barachant; Christian Jutten (EMBC, 2017)

Dimensionality Reduction for BCI Classification using Riemannian Geometry. - Pedro Luiz Coelho Rodrigues; Florent Bouchard; Marco Congedo; Christian Jutten (GBCIC, 2017)

Multivariate Time-Series Analysis Via Manifold Learning. - Pedro Luiz Coelho Rodrigues; Marco Congedo; Christian Jutten (SSP, 2018)

The Riemannian Minimum Distance to means field Classifier. - Marco Congedo; Pedro Rodrigues 002; Christian Jutten (GBCIC, 2019)

"When does it work ?" : An exploratory analysis of Transfer Learning for BCI. - Pedro Luiz Coelho Rodrigues; Marco Congedo; Christian Jutten (GBCIC, 2019)

Dataset of an EEG-based BCI experiment in Virtual Reality and on a Personal Computer. - Grégoire Cattan; Anton Andreev; Pedro C. Rodrigues; Marco Congedo (CoRR, 2019)

Passive Head-Mounted Display Music-Listening EEG dataset. - Grégoire Cattan; Pedro C. Rodrigues; Marco Congedo (CoRR, 2019)

Brain Invaders Adaptive versus Non-Adaptive P300 Brain-Computer Interface dataset. - Erwan Vaineau; Alexandre Barachant; Anton Andreev; Pedro C. Rodrigues; Grégoire Cattan; Marco Congedo (CoRR, 2019)

Building Brain Invaders: EEG data of an experimental validation. - Gijsbrecht Van Veen; Alexandre Barachant; Anton Andreev; Grégoire Cattan; Pedro Coelho Rodrigues; Marco Congedo (CoRR, 2019)

Riemannian Procrustes Analysis: Transfer Learning for Brain-Computer Interfaces. - Pedro Luiz Coelho Rodrigues; Christian Jutten; Marco Congedo (IEEE Trans. Biomed. Eng., 2019)

Learning summary features of time series for likelihood free inference. - Pedro L. C. Rodrigues; Alexandre Gramfort (CoRR, 2020)

Cytoarchitecture Measurements in Brain Gray Matter Using Likelihood-Free Inference. - Maëliss Jallais; Pedro L. C. Rodrigues; Alexandre Gramfort; Demian Wassermann (IPMI, 2021)

Guidelines to use Transfer Learning for Motor Imagery Detection: an experimental study. - Laurent Bougrain; Sébastien Rimbert; Pedro L. C. Rodrigues; Geoffrey Canron; Fabien Lotte (NER, 2021)

HNPE: Leveraging Global Parameters for Neural Posterior Estimation. - Pedro Rodrigues 002; Thomas Moreau 001; Gilles Louppe; Alexandre Gramfort (NeurIPS, 2021)

Leveraging Global Parameters for Flow-based Neural Posterior Estimation. - Pedro L. C. Rodrigues; Thomas Moreau 001; Gilles Louppe; Alexandre Gramfort (CoRR, 2021)

Inverting brain grey matter models with likelihood-free inference: a tool for trustable cytoarchitecture measurements. - Maëliss Jallais; Pedro Rodrigues 002; Alexandre Gramfort; Demian Wassermann (CoRR, 2021)

Dimensionality Transcending: A Method for Merging BCI Datasets With Different Dimensionalities. - Pedro L. C. Rodrigues; Marco Congedo; Christian Jutten (IEEE Trans. Biomed. Eng., 2021)

Validation Diagnostics for SBI algorithms based on Normalizing Flows. - Julia Linhart; Alexandre Gramfort; Pedro L. C. Rodrigues (CoRR, 2022)

pyRiemann/pyRiemann: v0.3. - Alexandre Barachant; Quentin Barthélemy; Jean-Rémi King; Alexandre Gramfort; Sylvain Chevallier; Pedro L. C. Rodrigues; Emanuele Olivetti; Vladislav Goncharenko; Gabriel Wagner vom Berg; Ghiles Reguig; Arthur Lebeurrier; Erik Bjäreholt; et al. (Zenodo, 2022)

L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inference. - Julia Linhart; Alexandre Gramfort; Pedro Rodrigues 002 (NeurIPS, 2023)

Diffusion posterior sampling for simulation-based inference in tall data settings. - Julia Linhart; Gabriel Victorino Cardoso; Alexandre Gramfort; Sylvain Le Corff; Pedro L. C. Rodrigues (CoRR, 2024)

Fast, accurate and lightweight sequential simulation-based inference using Gaussian locally linear mappings. - Henrik Häggström; Pedro L. C. Rodrigues; Geoffroy Oudoumanessah; Florence Forbes; Umberto Picchini (Trans. Mach. Learn. Res., 2024)

Methods and considerations for estimating parameters in biophysically detailed neural models with simulation based inference. - Nicholas Tolley; Pedro L. C. Rodrigues; Alexandre Gramfort; Stephanie R. Jones (PLoS Comput. Biol., 2024)

sbi reloaded: a toolkit for simulation-based inference workflows. - Jan Boelts; Michael Deistler; Manuel Glöckler; Álvaro Tejero-Cantero; Jan-Matthis Lueckmann; Guy Moss 001; Peter Steinbach; Thomas Moreau 001; Fabio Muratore; Julia Linhart; Conor Durkan; Julius Vetter; et al. (J. Open Source Softw., 2025)