Collaborative Machine Learning project with the Avant-garde Research Project (AARP)
We are pleased to announce a collaborative project with the Avant-garde Research Project (AARP), a not-for-profit organisation improving due-diligence standards in the area of the avant-garde.
Machine learning algorithms are able to detect patterns that our naked eyes cannot: for example, the average pressure with which an artist applies paint when producing broad or precise strokes, or the expected distances between compositional elements. The goal of this co-operative research project is to discover what we might learn about the works of avant-garde artists such Kazimir Malevich, El Lissitzky and Oleksandr Bohomazov, if machine learning were applied to their paintings.
To facilitate the project, Hephaestus and AARP are working closely with major public collections at the Stedelijk Museum (Amsterdam), Ludwig Museum (Cologne), Thyssen-Bornemisza Museum (Madrid), National Art Museum of Ukraine (Kyiv), as well as a number of private collectors, to collect data on bonafide, fully-authenticated paintings. These data points will form the backbone for the development of machine learning algorithms for use in the research of the avant-garde.