SIFT is an EEGLAB-compatible toolbox for analysis and visualization of multivariate causality and information flow between sources of electrophysiological (EEG/ECoG/MEG) activity. It consists of a suite of command-line functions with an integrated Graphical User Interface for easy access to multiple features. There are currently six modules: dat…
This repository contains the code for the paper "Sentiment-driven statistical causality in multimodal systems", by Ioannis Chalkiadakis, Anna Zaremba, Gareth W. Peters and Michael J. Chantler.
Simulation of integrated information in biological systems.
Pipeline for inference of Granger-causal relations in molecular systems to study actin regulation in lamellipodia
A toolset for evaluating the results and impacts of an educational event, employing cognitive maps as a model for representing cognitive structures or knowledge.
Reproducible code for our paper, "On Causal Discovery with Convergent Cross Mapping"
Reproducible code for our paper "Measuring Strength of Joint Causal Effects", IEEE TSP 2024.
Interpolation functions for a discrete signal
Implementation of the algorithms from "Learning Invariant Representations under General Interventions on the Response"
The Method of Entropic Regression, sparse system identification method based on causality inference of complex networks.
Reproducible code for our paper "A Differential Measure of the Strength of Causation"
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