Wimmer, Lisa

8 publications

ICLRW 2025 Trust Me, I Know the Way: Predictive Uncertainty in the Presence of Shortcut Learning Lisa Wimmer, Bernd Bischl, Ludwig Bothmann

ICML 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

ECML-PKDD 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

UAI 2024 Label-Wise Aleatoric and Epistemic Uncertainty Quantification Yusuf Sale, Paul Hofman, Timo Löhr, Lisa Wimmer, Thomas Nagler, Eyke Hüllermeier

ICLR 2024 Probabilistic Self-Supervised Representation Learning via Scoring Rules Minimization Amirhossein Vahidi, Simon Schosser, Lisa Wimmer, Yawei Li, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei

IJCAI 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

UAI 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

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