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Lisa Wimmer
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Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning: Are Conditional Entropy and Mutual Information Appropriate Measures?
L Wimmer, Y Sale, P Hofman, B Bischl, E Hüllermeier
39th Conference on Uncertainty in Artificial Intelligence (UAI 2023), 2023
212023
Automated wildlife image classification: An active learning tool for ecological applications
L Bothmann, L Wimmer, O Charrakh, T Weber, H Edelhoff, W Peters, ...
Ecological Informatics 77 (102231), 2023
82023
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry
JG Wiese, L Wimmer, T Papamarkou, B Bischl, S Günnemann, ...
ECML-PKDD 2023, 2023
42023
Second-Order Uncertainty Quantification: Variance-Based Measures
Y Sale, P Hofman, L Wimmer, E Hüllermeier, T Nagler
arXiv preprint arXiv:2401.00276, 2023
32023
Probabilistic Self-supervised Learning via Scoring Rules Minimization
A Vahidi, S Schoßer, L Wimmer, Y Li, B Bischl, E Hüllermeier, M Rezaei
ICLR 2024, 2024
12024
Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?
E Sommer, L Wimmer, T Papamarkou, L Bothmann, B Bischl, D Rügamer
arXiv preprint arXiv:2402.01484, 2024
2024
Quantifying aleatoric and epistemic uncertainty in medical image classification with deep neural networks
L Wimmer
University of Munich (LMU), 2021
2021
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