Aesthetical issues of Leonardo Da Vinci’s and Pablo Picasso’s paintings with stochastic evaluation

G.-F. Sargentis, P. Dimitriadis, and D. Koutsoyiannis, Aesthetical issues of Leonardo Da Vinci’s and Pablo Picasso’s paintings with stochastic evaluation, Heritage, 3 (2), 283–305, doi:10.3390/heritage3020017, 2020.



A physical process is characterized as complex when it is difficult to analyze or explain in a simple way. The complexity within an art painting is expected to be high, possibly comparable to that of nature. Therefore, constructions of artists (e.g., paintings, music, literature, etc.) are expected to be also of high complexity since they are produced by numerous human (e.g., logic, instinct, emotions, etc.) and non-human (e.g., quality of paints, paper, tools, etc.) processes interacting with each other in a complex manner. The result of the interaction among various processes is not a white-noise behavior, but one where clusters of high or low values of quantified attributes appear in a non-predictive manner, thus highly increasing the uncertainty and the variability. In this work, we analyze stochastic patterns in terms of the dependence structure of art paintings of Da Vinci and Picasso with a stochastic 2D tool and investigate the similarities or differences among the artworks.

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Our works referenced by this work:

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8. G.-F. Sargentis, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, and D. Koutsoyiannis, Stochastic investigation of the Hurst-Kolmogorov behaviour in arts, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17740-1, European Geosciences Union, 2018.
9. P. Dimitriadis, K. Tzouka, D. Koutsoyiannis, H. Tyralis, A. Kalamioti, E. Lerias, and P. Voudouris, Stochastic investigation of long-term persistence in two-dimensional images of rocks, Spatial Statistics, 29, 177–191, doi:10.1016/j.spasta.2018.11.002, 2019.
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Our works that reference this work:

1. G.-F. Sargentis, T. Iliopoulou, S. Sigourou, P. Dimitriadis, and D. Koutsoyiannis, Evolution of clustering quantified by a stochastic method — Case studies on natural and human social structures, Sustainability, 12 (19), 7972, doi:10.3390/su12197972, 2020.
2. G.-F. Sargentis, R. Ioannidis, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Landscape planning of infrastructure through focus points’ clustering analysis. Case study: Plastiras artificial lake (Greece), Infrastructures, 6 (1), 12, doi:10.3390/infrastructures6010012, 2021.
3. P. Dimitriadis, D. Koutsoyiannis, T. Iliopoulou, and P. Papanicolaou, A global-scale investigation of stochastic similarities in marginal distribution and dependence structure of key hydrological-cycle processes, Hydrology, 8 (2), 59, doi:10.3390/hydrology8020059, 2021.

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