\(\mathrm{SL}(2,\mathbb{Z})\)-equivariant machine learning with modular forms theory and applications

DOI10.1007/978-3-031-38299-4_63OpenAlexW4385435168MaRDI QIDQ6179066

Pierre-Yves Lagrave

Publication date: 16 January 2024

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-031-38299-4_63

zbMATH Keywords

quantitative financeequivariant machine learningmodular forms theory

Mathematics Subject Classification ID

Computational learning theory (68Q32) Learning and adaptive systems in artificial intelligence (68T05) Financial applications of other theories (91G80) Other groups and their modular and automorphic forms (several variables) (11F55)

Cites Work

• Equivariant functions and integrals of elliptic functions
• \(\mathrm{SU}(1,1)\) equivariant neural networks and application to robust Toeplitz Hermitian positive definite matrix classification
• Equivariant Forms: Structure and Geometry
• RATIONAL EQUIVARIANT FORMS
• A Review of Two Decades of Correlations, Hierarchies, Networks and Clustering in Financial Markets
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