533 citations · 1.7k across the 63 of their papers we have counts for
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Data for Mathematical Copilots: Better Ways of Presenting Proofs for Machine Learning
Simon Frieder, Jonas Bayer, Sam Looi +13
The datasets and benchmarks commonly used to train and evaluate the mathematical capabilities of AI-based mathematical copilots (primarily large language models) exhibit several sh…
A Twist on Heterotic Little String Duality
Hamza Ahmed, Paul-Konstantin Oehlmann, Fabian Ruehle
In this work, we significantly expand the web of T-dualities among heterotic NS5-brane theories with eight supercharges. This is achieved by introducing twists involving outer auto…
Attractors, Geodesics, and the Geometry of Moduli Spaces
Fabian Ruehle, Benjamin Sung
We connect recent conjectures and observations pertaining to geodesics, attractor flows, Laplacian eigenvalues and the geometry of moduli spaces by using that attractor flows are g…
A Heterotic Kähler Gravity and the Distance Conjecture
Javier José Murgas Ibarra, Paul-Konstantin Oehlmann, Fabian Ruehle +1
Deformations of the heterotic superpotential give rise to a topological holomorphic theory with similarities to both Kodaira-Spencer gravity and holomorphic Chern-Simons theory. Al…
Bounds and Dualities of Type II Little String Theories
Florent Baume, Paul-Konstantin Oehlmann, Fabian Ruehle
We explore the symmetry structure of Type II Little String Theories and their T-dualities. We construct these theories both from the bottom-up perspective starting with seed Superc…
The Frozen Phase of Heterotic F-theory Duality
Paul-Konstantin Oehlmann, Fabian Ruehle, Benjamin Sung
We study the duality between the Spin heterotic string without vector structure and F-theory with frozen singularities. We give a complete description in theorie…
KAN: Kolmogorov-Arnold Networks
Ziming Liu, Yixuan Wang, Sachin Vaidya +5
Inspired by the Kolmogorov-Arnold representation theorem, we propose Kolmogorov-Arnold Networks (KANs) as promising alternatives to Multi-Layer Perceptrons (MLPs). While MLPs have…
On classical de Sitter solutions and parametric control
David Andriot, Fabian Ruehle
Finding string backgrounds with de Sitter spacetime, where all approximations and corrections are controlled, is an open problem. We revisit the search for de Sitter solutions in t…
Rigor with Machine Learning from Field Theory to the Poincaré Conjecture
Sergei Gukov, James Halverson, Fabian Ruehle
Machine learning techniques are increasingly powerful, leading to many breakthroughs in the natural sciences, but they are often stochastic, error-prone, and blackbox. How, then, s…