Lisa Wimmer

According to our database, Lisa Wimmer authored at least 14 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

On the analysis of spectral deferred corrections for differential-algebraic equations of index one.

Matthias Bolten, Lisa Wimmer

CoRR, January, 2026

2025

Trust Me, I Know the Way: Predictive Uncertainty in the Presence of Shortcut Learning.

Lisa Wimmer, Bernd Bischl, Ludwig Bothmann

CoRR, February, 2025

Representing and quantifying predictive uncertainty in machine learning.

Lisa Wimmer

PhD thesis, 2025

2024

Second-Order Uncertainty Quantification: Variance-Based Measures.

Yusuf Sale, Paul Hofman, Lisa Wimmer, Eyke Hüllermeier, Thomas Nagler

CoRR, 2024

Label-wise Aleatoric and Epistemic Uncertainty Quantification.

Yusuf Sale, Paul Hofman, Timo Löhr, Lisa Wimmer, Thomas Nagler, Eyke Hüllermeier

Proceedings of the Uncertainty in Artificial Intelligence, 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

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 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

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization.

Amirhossein Vahidi, Simon Schoßer, Lisa Wimmer, Yawei Li, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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, November, 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

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

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

Proceedings of the Uncertainty in Artificial Intelligence, 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

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023