Yusuf Sale

Ph.D. candidate at LMU Munich. Statistician.

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I am currently working on mathematical and statistical foundations of Uncertainty Quantification and Representation in Artificial Intelligence (AI) and Machine Learning (ML). My research aims at developing reliable and trustworthy AI and ML systems capable of accounting for inherent uncertainties in their predictions, thereby providing more reliable decision-making tools across a broad range of applications.

Moreover, I am interested in generalized notions of probability, which are persuasive in representing uncertainty in ML applications. Since such theories under a generalized notion of probability require proper uncertainty quantification, I am also investigating suitable measures of uncertainty from theoretical and practical perspectives.

I am a member of the Konrad Zuse School of Excellence in Reliable AI (relAI), sponsored by the Federal Ministry of Education and Research.

News

Jul 25, 2024 We presented our spotlight poster at ICML 2024 in Vienna. It was fantastic to present our paper and connect with the machine learning community. :austria:
Jul 16, 2024 We presented our poster at UAI 2024 in Barcelona. The engaging discussions were truly inspiring. :es:
May 15, 2022 Excited to announce that I have joined the AI+ML chair at LMU Munich for my Ph.D. under the supervision of Eyke Hüllermeier. :mortar_board:

Selected Publications

  1. UAI
    Label-wise Aleatoric and Epistemic Uncertainty Quantification
    Yusuf Sale, Paul Hofman, Timo Löhr, and 3 more authors
    In The 40th Conference on Uncertainty in Artificial Intelligence, 2024
  2. UAI
    Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning: Are Conditional Entropy and Mutual Information Appropriate Measures?
    Lisa Wimmer, Yusuf Sale, Paul Hofman, and 2 more authors
    In The 39th Conference on Uncertainty in Artificial Intelligence, 2023
  3. UAI
    Is the Volume of a Credal Set a Good Measure for Epistemic Uncertainty?
    Yusuf Sale, Michele Caprio, and Eyke Hüllermeier
    In The 39th Conference on Uncertainty in Artificial Intelligence, 2023
  4. ICML
    Second-Order Uncertainty Quantification: A Distance-Based Approach
    Yusuf Sale, Viktor Bengs, Michele Caprio, and 1 more author
    In Forty-first International Conference on Machine Learning, 2024
  5. COPA
    Conformal Prediction with Partially Labeled Data
    Alireza Javanmardi, Yusuf Sale, Paul Hofman, and 1 more author
    In Conformal and Probabilistic Prediction with Applications, 2023
  6. SPIGM
    Quantifying Aleatoric and Epistemic Uncertainty: A Credal Approach
    Paul Hofman, Yusuf Sale, and Eyke Hüllermeier
    In ICML 2024 Workshop on Structured Probabilistic Inference & Generative Modeling, 2024
  7. THESIS
    G-Framework in Statistics
    Yusuf Sale
    2022
  8. Epi UAI
    A Novel Bayes’ Theorem for Upper Probabilities
    Michele Caprio, Yusuf Sale, Eyke Hüllermeier, and 1 more author
    In International Workshop on Epistemic Uncertainty in Artificial Intelligence, 2023