40 citations · 50 across the 5 of their papers we have counts for
5 papers
Why is the prediction wrong? Towards underfitting case explanation via meta-classification
Sheng Zhou, Pierre Blanchart, Michel Crucianu +1
In this paper we present a heuristic method to provide individual explanations for those elements in a dataset (data points) which are wrongly predicted by a given classifier. Sinc…
Deep learning for ECoG brain-computer interface: end-to-end vs. hand-crafted features
Maciej Śliwowski, Matthieu Martin, Antoine Souloumiac +2
In brain signal processing, deep learning (DL) models have become commonly used. However, the performance gain from using end-to-end DL models compared to conventional ML approache…
Impact of dataset size and long-term ECoG-based BCI usage on deep learning decoders performance
Maciej Śliwowski, Matthieu Martin, Antoine Souloumiac +2
In brain-computer interfaces (BCI) research, recording data is time-consuming and expensive, which limits access to big datasets. This may influence the BCI system performance as m…
Decoding ECoG signal into 3D hand translation using deep learning
Maciej Śliwowski, Matthieu Martin, Antoine Souloumiac +2
Motor brain-computer interfaces (BCIs) are a promising technology that may enable motor-impaired people to interact with their environment. Designing real-time and accurate BCI is…
An exact counterfactual-example-based approach to tree-ensemble models interpretability
Pierre Blanchart
Explaining the decisions of machine learning models is becoming a necessity in many areas where trust in ML models decision is key to their accreditation/adoption. The ability to e…