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University of Cambridge > Talks.cam > Algebraic Geometry Seminar > Machine learning detects terminal singularities
Machine learning detects terminal singularitiesAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Holly Krieger. In this talk, I will describe recent work in the application of machine learning to explore questions in algebraic geometry, specifically in the context of the study of Q-Fano varieties. These are Q-factorial terminal Fano varieties, and they are the key players in the Minimal Model Program. In this work, we ask and answer if machine learning can determine if a toric Fano variety has terminal singularities. We build a high-accuracy neural network that detects this, which has two consequences. Firstly, it inspires the formulation and proof of a new global, combinatorial criterion to determine if a toric variety of Picard rank two has terminal singularities. Secondly, the machine learning model is used directly to give the first sketch of the landscape of Q-Fano varieties in dimension eight. This is joint work with Tom Coates and Al Kasprzyk. This talk is part of the Algebraic Geometry Seminar series. This talk is included in these lists:
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