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An open-source and easy-to-use Python platform for offline neurophysiological signals processing and classification

Eye-movement analysis with hidden semi-Markov models to segment phases in reading tasks

Source code for the paper "Successor Feature Representations".

Correcting estimations of copepod volume from 2-dimensional images

OPS: Off-the-grid Package made Simple. It provides the framework and essential functions for numerical gridless algorithms

Crash data analysis with hidden Markov random fields with Bayesian Nonparametric priors.

Code and experiments for the paper "Successor Feature Neural Episodic Control"

Experiment code for the paper "Merkle Search Trees: Efficient State-Based CRDTs in Open Networks"