Identifiability Results for Multimodal Contrastive Learning. - Imant Daunhawer; Alice Bizeul; Emanuele Palumbo; Alexander Marx 001; Julia E. Vogt (ICLR, 2023)

A Probabilistic Model to explain Self-Supervised Representation Learning. - Alice Bizeul; Bernhard Schölkopf; Carl Allen (CoRR, 2024)

A Probabilistic Model behind Self- Supervised Learning. - Alice Bizeul; Bernhard Schölkopf; Carl Allen (Trans. Mach. Learn. Res., 2024)

Cross-Entropy Is All You Need To Invert the Data Generating Process. - Patrik Reizinger; Alice Bizeul; Attila Juhos; Julia E. Vogt; Randall Balestriero; Wieland Brendel; David A. Klindt (ICLR, 2025)

From Pixels to Components: Eigenvector Masking for Visual Representation Learning. - Alice Bizeul; Thomas M. Sutter; Alain Ryser; Bernhard Schölkopf; Julius von Kügelgen; Julia E. Vogt (CoRR, 2025)

Interpretable Diffusion Models with B-cos Networks. - Nicola Bernold; Moritz Vandenhirtz; Alice Bizeul; Julia E. Vogt (CoRR, 2025)