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Viktor Bengs
Viktor Bengs
6
papers
135
total citations
papers (6)
Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation
NEURIPS 2022
arXiv
55
citations
Approximating the Shapley Value without Marginal Contributions
AAAI 2024
arXiv
39
citations
Second-Order Uncertainty Quantification: A Distance-Based Approach
ICML 2024
arXiv
33
citations
Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget
NEURIPS 2022
arXiv
8
citations
Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?
ICML 2024
0
citations
Identification of the Generalized Condorcet Winner in Multi-dueling Bandits
NEURIPS 2021
0
citations