activity
20152024
most citedLow Algorithmic Complexity Entropy-deceiving Graphs

85 citations · 105 across the 7 of their papers we have counts for

collaborators

7 papers

cs.IT2024★ 2 cited

Assembly Theory Reduced to Shannon Entropy and Rendered Redundant by Naive Statistical Algorithms

Luan Ozelim, Abicumaran Uthamacumaran, Felipe S. Abrahão +4

Assembly Theory (AT) and its central measure, the assembly index (Ai), represent an invaluable opportunity to address some of the most persistent and widespread conflations and mis…

cs.IT2024★ 1 cited

Assembly Theory is an approximation to algorithmic complexity based on LZ compression that does not explain selection or evolution

Felipe S. Abrahão, Santiago Hernández-Orozco, Narsis A. Kiani +2

We prove the full equivalence between Assembly Theory (AT) and Shannon Entropy via a method based upon the principles of statistical compression renamed `assembly index' that belon…

cs.AI2023★ 11 cited

The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence

Hector Zenil, Jesper Tegnér, Felipe S. Abrahão +17

Recent advances in machine learning and AI, including Generative AI and LLMs, are disrupting technological innovation, product development, and society as a whole. AI's contributio…

q-bio.NC2019

Estimations of Integrated Information Based on Algorithmic Complexity and Dynamic Querying

Alberto Hernández-Espinosa, Héctor Zenil, Narsis A. Kiani +1

The concept of information has emerged as a language in its own right, bridging several disciplines that analyze natural phenomena and man-made systems. Integrated information has…

cs.DS2018★ 5 cited

Minimal Algorithmic Information Loss Methods for Dimension Reduction, Feature Selection and Network Sparsification

Hector Zenil, Narsis A. Kiani, Alyssa Adams +5

We present a novel, domain-agnostic, model-independent, unsupervised, and universally applicable Machine Learning approach for dimensionality reduction based on the principles of a…

cs.IT2016★ 85 cited

Low Algorithmic Complexity Entropy-deceiving Graphs

Hector Zenil, Narsis Kiani, Jesper Tegnér

In estimating the complexity of objects, in particular of graphs, it is common practice to rely on graph- and information-theoretic measures. Here, using integer sequences with pro…

cs.NE2015★ 1 cited

Causality, Information and Biological Computation: An algorithmic software approach to life, disease and the immune system

Hector Zenil, Angelika Schmidt, Jesper Tegnér

Biology has taken strong steps towards becoming a computer science aiming at reprogramming nature after the realisation that nature herself has reprogrammed organisms by harnessing…