Hector Zenil
Hector Zenil
Associate Professor @ King’s College London & ISA UK Innovate AI Advisor @ The Alan Turing Institute
Verified email at - Homepage
Cited by
Cited by
Inferring causal molecular networks: empirical assessment through a community-based effort
SM Hill, LM Heiser, T Cokelaer, M Unger, NK Nesser, DE Carlin, Y Zhang, ...
Nature methods 13 (4), 310-318, 2016
Calculating Kolmogorov complexity from the output frequency distributions of small turing machines
F Soler-Toscano, H Zenil, JP Delahaye, N Gauvrit
PLoS ONE 9 (5), e96223, 2014
Numerical Evaluation of the Complexity of Short Strings: A Glance Into the Innermost Structure of Algorithmic Randomness
H Zenil, JP Delahaye
Applied Mathematics and Computation 219, 63-77, 2011
Algorithmic complexity of motifs clusters superfamilies of networks
H Zenil, NA Kiani, J Tegnér
2013 IEEE international conference on bioinformatics and biomedicine, 74-76, 2013
A decomposition method for global evaluation of Shannon entropy and local estimations of algorithmic complexity
H Zenil, S Hernández-Orozco, N Kiani, F Soler-Toscano, A Rueda-Toicen, ...
Entropy 20 (8), 605, 2018
A Computable Universe: Understanding and Exploring Nature as Computation
H Zenil
World Scientific Publishing Company, 2012
Compression-based investigation of the dynamical properties of cellular automata and other systems
H Zenil
Complex Systems 19 (1), 1-28, 2010
Correlation of automorphism group size and topological properties with program-size complexity evaluations of graphs and complex networks
H Zenil, F Soler-Toscano, K Dingle, AA Louis
Physica A: Statistical Mechanics and its Applications 404, 341-358, 2014
Slime mould: the fundamental mechanisms of biological cognition
J Vallverdú, O Castro, R Mayne, M Talanov, M Levin, F Baluška, Y Gunji, ...
Biosystems 165, 57-70, 2018
Simulation intelligence: Towards a new generation of scientific methods
A Lavin, D Krakauer, H Zenil, J Gottschlich, T Mattson, J Brehmer, ...
arXiv preprint arXiv:2112.03235, 2021
Causal Deconvolution by Algorithmic Generative Models
H Zenil, NA Kiani, A Zea, J Tegnér
Nature Machine Learning 1, 2019
Low-algorithmic-complexity entropy-deceiving graphs
H Zenil, NA Kiani, J Tegnér
Physical Review E 96 (1), 012308, 2017
Two-dimensional Kolmogorov complexity and an empirical validation of the Coding theorem method by compressibility
H Zenil, F Soler-Toscano, JP Delahaye, N Gauvrit
PeerJ Computer Science 1, e23, 2015
A review of graph and network complexity from an algorithmic information perspective
H Zenil, NA Kiani, J Tegnér
Entropy 20 (8), 551, 2018
Methods of information theory and algorithmic complexity for network biology
H Zenil, NA Kiani, J Tegnér
Seminars in Cell and Developmental Biology 51, 32-43, 2016
Formal definitions of unbounded evolution and innovation reveal universal mechanisms for open-ended evolution in dynamical systems
A Adams, H Zenil, PCW Davies, SI Walker
Scientific reports 7 (1), 997, 2017
Asymptotic Behaviour and Ratios of Complexity in Cellular Automata
H Zenil
International Journal of Bifurcation and Chaos 23 (9), 2013
Algorithmic complexity for short binary strings applied to psychology: a primer
N Gauvrit, H Zenil, JP Delahaye, F Soler-Toscano
Behavior Research Methods 46 (3), 732-744, 2014
Algorithmic complexity for psychology: A user-friendly implementation of the coding theorem method
N Gauvrit, H Singmann, F Soler-Toscano, H Zenil
Behavior Research Methods 48 (1), 1-16, 2015
Human behavioral complexity peaks at age 25
N Gauvrit, H Zenil, F Soler-Toscano, JP Delahaye, P Brugger
PLoS computational biology 13 (4), e1005408, 2017
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