A neural network approach to predicting and computing knot invariants

DOI10.1142/S0218216520500054zbMath1439.57015arXiv1610.05744OpenAlexW3003920098MaRDI QIDQ5111763

Mark C. Hughes

Publication date: 27 May 2020

Published in: Journal of Knot Theory and Its Ramifications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1610.05744

zbMATH Keywords

neural networksknotsknot invariants

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Knot theory (57K10)

Related Items

Rectangular knot diagrams classification with deep learning ⋮ Big data approaches to knot theory: Understanding the structure of the Jones polynomial ⋮ Narrowing the gap between combinatorial and hyperbolic knot invariants via deep learning

Uses Software

• Theano
• KnotInfo
• Keras
• HFK
• Adam
• GitHub

Cites Work

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• Khovanov homology and the slice genus
• Braided surfaces and Seifert ribbons for closed braids
• Knot Floer homology and the four-ball genus
• Bounds for the Thurston-Bennequin number from Floer homology
• A combinatorial description of knot Floer homology
• Singularities of 2-spheres in 4-space and cobordism of knots
• COMPUTATIONS OF HEEGAARD-FLOER KNOT HOMOLOGY
• Quasipositivity as an obstruction to sliceness