DNN-based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel. - Benjamin Dupuis; Arthur Jacot (NeurIPS, 2021)

Generalization Bounds using Data-Dependent Fractal Dimensions. - Benjamin Dupuis; George Deligiannidis; Umut Simsekli (ICML, 2023)

Generalization Bounds with Data-dependent Fractal Dimensions. - Benjamin Dupuis; George Deligiannidis; Umut Simsekli (CoRR, 2023)

From Mutual Information to Expected Dynamics: New Generalization Bounds for Heavy-Tailed SGD. - Benjamin Dupuis; Paul Viallard (CoRR, 2023)

Generalization Bounds for Heavy-Tailed SDEs through the Fractional Fokker-Planck Equation. - Benjamin Dupuis; Umut Simsekli (ICML, 2024)

Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms. - Rayna Andreeva; Benjamin Dupuis; Rik Sarkar; Tolga Birdal; Umut Simsekli (NeurIPS, 2024)

Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets. - Benjamin Dupuis; Paul Viallard; George Deligiannidis; Umut Simsekli (CoRR, 2024)

Understanding the Generalization Error of Markov algorithms through Poissonization. - Benjamin Dupuis; Maxime Haddouche; George Deligiannidis; Umut Simsekli (CoRR, 2025)

Algorithm- and Data-Dependent Generalization Bounds for Score-Based Generative Models. - Benjamin Dupuis; Dario Shariatian; Maxime Haddouche; Alain Durmus; Umut Simsekli (CoRR, 2025)

Mutual Information Free Topological Generalization Bounds via Stability. - Mario Tuci; Lennart Bastian; Benjamin Dupuis; Nassir Navab; Tolga Birdal; Umut Simsekli (CoRR, 2025)