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Machine Learning Detects Terminal Singularities in Q-Fano Varieties

Offered By: Applied Algebraic Topology Network via YouTube

Tags

Machine Learning Courses Neural Networks Courses Combinatorics Courses Topology Courses Algebraic Geometry Courses Minimal Model Program Courses Toric Varieties Courses

Course Description

Overview

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Explore the intersection of machine learning and algebraic geometry in this 48-minute talk from the Applied Algebraic Topology Network. Delve into the application of neural networks to study Q-Fano varieties, key components in the Minimal Model Program. Learn how a high-accuracy machine learning model was developed to detect terminal singularities in toric Fano varieties, leading to two significant outcomes: the formulation of a new combinatorial criterion for determining terminal singularities in Picard rank two toric varieties, and the first glimpse into the landscape of eight-dimensional Q-Fano varieties. Gain insights into this collaborative research effort that bridges advanced mathematics and cutting-edge machine learning techniques.

Syllabus

Sara Veneziale (09/18/24): Machine learning detects terminal singularities


Taught by

Applied Algebraic Topology Network

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