Learning Size and Shape of Calabi-Yau Spaces. - Magdalena Larfors; André Lukas; Fabian Ruehle; Robin Schneider (CoRR, 2021)

Learning to unknot. - Sergei Gukov; James Halverson; Fabian Ruehle; Piotr Sulkowski (Mach. Learn. Sci. Technol., 2021)

Numerical metrics for complete intersection and Kreuzer-Skarke Calabi-Yau manifolds. - Magdalena Larfors; André Lukas; Fabian Ruehle; Robin Schneider (Mach. Learn. Sci. Technol., 2022)

Searching for ribbons with machine learning. - Sergei Gukov; James Halverson; Ciprian Manolescu; Fabian Ruehle (CoRR, 2023)

Rigor with Machine Learning from Field Theory to the Poincaré Conjecture. - Sergei Gukov; James Halverson; Fabian Ruehle (CoRR, 2024)

Data for Mathematical Copilots: Better Ways of Presenting Proofs for Machine Learning. - Simon Frieder; Jonas Bayer; Katherine M. Collins; Julius Berner; Jacob Loader; András Juhász; Fabian Ruehle; Sean Welleck; Gabriel Poesia; Ryan-Rhys Griffiths; Adrian Weller; Anirudh Goyal; et al. (CoRR, 2024)

Metric flows with neural networks. - James Halverson; Fabian Ruehle (Mach. Learn. Sci. Technol., 2024)

KAN: Kolmogorov-Arnold Networks. - Ziming Liu; Yixuan Wang; Sachin Vaidya; Fabian Ruehle; James Halverson; Marin Soljacic; Thomas Y. Hou 001; Max Tegmark (ICLR, 2025)

Interpretable Machine Learning for Kronecker Coefficients. - Giorgi Butbaia; Kyu-Hwan Lee; Fabian Ruehle (CoRR, 2025)

On the Learnability of Knot Invariants: Representation, Predictability, and Neural Similarity. - Audrey Lindsay; Fabian Ruehle (CoRR, 2025)

Symbolic Regression with Multimodal Large Language Models and Kolmogorov Arnold Networks. - Thomas R. Harvey; Fabian Ruehle; Cristofero S. Fraser-Taliente; James Halverson (CoRR, 2025)

Improving Generative Inverse Design of Rectangular Patch Antennas with Test Time Optimization. - Beck LaBash; Shahriar Khushrushahi; Fabian Ruehle (CoRR, 2025)