21 citations · 73 across the 25 of their papers we have counts for
5 papers · 1 filter
Evaluating Network Inference Methods in Terms of Their Ability to Preserve the Topology and Complexity of Genetic Networks
Narsis A. Kiani, Hector Zenil, Jakub Olczak +1
Network inference is a rapidly advancing field, with new methods being proposed on a regular basis. Understanding the advantages and limitations of different network inference meth…
Approximations of Algorithmic and Structural Complexity Validate Cognitive-behavioural Experimental Results
Hector Zenil, James A. R. Marshall, Jesper Tegnér
Being able to objectively characterise the intrinsic complexity of behavioural patterns resulting from human or animal decisions is fundamental for deconvolving cognition and desig…
Quantifying Loss of Information in Network-based Dimensionality Reduction Techniques
Hector Zenil, Narsis A. Kiani, Jesper Tegnér
To cope with the complexity of large networks, a number of dimensionality reduction techniques for graphs have been developed. However, the extent to which information is lost or p…
Numerical Investigation of Graph Spectra and Information Interpretability of Eigenvalues
Hector Zenil, Narsis A. Kiani, Jesper Tegnér
We undertake an extensive numerical investigation of the graph spectra of thousands regular graphs, a set of random Erdös-Rényi graphs, the two most popular types of complex networ…
The Information-theoretic and Algorithmic Approach to Human, Animal and Artificial Cognition
Nicolas Gauvrit, Hector Zenil, Jesper Tegnér
We survey concepts at the frontier of research connecting artificial, animal and human cognition to computation and information processing---from the Turing test to Searle's Chines…