Random matrix analysis of deep neural network weight matrices. - Matthias Thamm; Max Staats; Bernd Rosenow (CoRR, 2022)

Boundary between noise and information applied to filtering neural network weight matrices. - Max Staats; Matthias Thamm; Bernd Rosenow (CoRR, 2022)

Machine learning optimization of Majorana hybrid nanowires. - Matthias Thamm; Bernd Rosenow (CoRR, 2022)

Topological gap protocol based machine learning optimization of Majorana hybrid wires. - Matthias Thamm; Bernd Rosenow (CoRR, 2023)

Reevaluating Loss Functions: Enhancing Robustness to Label Noise in Deep Learning Models. - Max Staats; Matthias Thamm; Bernd Rosenow (CoRR, 2023)

Locating Information in Large Language Models via Random Matrix Theory. - Max Staats; Matthias Thamm; Bernd Rosenow (CoRR, 2024)

Enhancing Noise-Robust Losses for Large-Scale Noisy Data Learning. - Max Staats; Matthias Thamm; Bernd Rosenow (AAAI, 2025)