Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry. - Jonas Gregor Wiese; Lisa Wimmer; Theodore Papamarkou; Bernd Bischl; Stephan Günnemann; David Rügamer (ECML/PKDD (1), 2023)

Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures? - Lisa Wimmer; Yusuf Sale; Paul Hofman; Bernd Bischl; Eyke Hüllermeier (UAI, 2023)

Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning. - Amirhossein Vahidi; Lisa Wimmer; Hüseyin Anil Gündüz; Bernd Bischl; Eyke Hüllermeier; Mina Rezaei (CoRR, 2023)

Probabilistic Self-supervised Learning via Scoring Rules Minimization. - Amirhossein Vahidi; Simon Schoßer; Lisa Wimmer; Yawei Li; Bernd Bischl; Eyke Hüllermeier; Mina Rezaei (CoRR, 2023)

Automated wildlife image classification: An active learning tool for ecological applications. - Ludwig Bothmann; Lisa Wimmer; Omid Charrakh; Tobias Weber; Hendrik Edelhoff; Wibke Peters; Hien Nguyen; Caryl Benjamin; Annette Menzel (Ecol. Informatics, 2023)

Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization. - Amirhossein Vahidi; Simon Schoßer; Lisa Wimmer; Yawei Li; Bernd Bischl; Eyke Hüllermeier; Mina Rezaei (ICLR, 2024)

Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks? - Emanuel Sommer; Lisa Wimmer; Theodore Papamarkou; Ludwig Bothmann; Bernd Bischl; David Rügamer (ICML, 2024)

Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry (Extended Abstract). - Jonas Gregor Wiese; Lisa Wimmer; Theodore Papamarkou; Bernd Bischl; Stephan Günnemann; David Rügamer (IJCAI, 2024)

Diversified Ensemble of Independent Sub-networks for Robust Self-supervised Representation Learning. - Amihossein Vahidi; Lisa Wimmer; Hüseyin Anil Gündüz; Bernd Bischl; Eyke Hüllermeier; Mina Rezaei (ECML/PKDD (1), 2024)

Label-wise Aleatoric and Epistemic Uncertainty Quantification. - Yusuf Sale; Paul Hofman; Timo Löhr; Lisa Wimmer; Thomas Nagler; Eyke Hüllermeier (UAI, 2024)

Second-Order Uncertainty Quantification: Variance-Based Measures. - Yusuf Sale; Paul Hofman; Lisa Wimmer; Eyke Hüllermeier; Thomas Nagler (CoRR, 2024)

Trust Me, I Know the Way: Predictive Uncertainty in the Presence of Shortcut Learning. - Lisa Wimmer; Bernd Bischl; Ludwig Bothmann (CoRR, 2025)