Scholar
Yusuf Sale
Google Scholar ID: yn3w9eoAAAAJ
LMU Munich, MCML, relAI Konrad Zuse School
Statistics
Uncertainty Quantification
Machine Learning
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Citations & Impact
All-time
Citations
298
H-index
9
i10-index
9
Publications
20
Co-authors
21
list available
Publications
12 items
What Uncertainties Do We Need for Dynamical Systems?
2026
Cited
0
Position: agentic AI orchestration should be Bayes-consistent
2026
Cited
0
Quantification of Credal Uncertainty: A Distance-Based Approach
2026
Cited
0
Efficient Credal Prediction through Decalibration
2026
Cited
0
Quantifying Epistemic Predictive Uncertainty in Conformal Prediction
2026
Cited
0
Uncertainty Quantification for Machine Learning: One Size Does Not Fit All
2025
Cited
0
Uncertainty Quantification for Regression: A Unified Framework based on kernel scores
2025
Cited
0
Uncertainty Quantification with Proper Scoring Rules: Adjusting Measures to Prediction Tasks
2025
Cited
0
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Co-authors
16 total
Eyke Hüllermeier
Professor of Computer Science, Paderborn University
Paul Hofman
Ludwig Maximilian University of Munich
Michele Caprio
Lecturer (Asst. Prof.), The University of Manchester
Lisa Wimmer
PhD student @LMU Munich | Munich Center for Machine Learning (MCML) | relAI Konrad Zuse School
Bernd Bischl
Chair of Statistical Learning and Data Science, LMU Munich
Thomas Nagler
LMU Munich, Munich Center for Machine Learning
Alireza Javanmardi
LMU Munich, MCML
Viktor Bengs
German Research Center for Artificial Intelligence (DFKI)
