Publications

2024

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    Deep Classifier Mimicry without Data Access
    Steven Braun, Martin Mundt, and Kristian Kersting
    International Conference on Artificial Intelligence and Statistics (AISTATS) – Oral & Student Paper Highlight Award, 2024

2023

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    Probabilistic Circuits That Know What They Don’t Know
    Fabrizio Ventola*, Steven Braun*, Zhongjie Yu, Martin Mundt, and Kristian Kersting
    Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence (UAI), 2023

2022

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    Towards Coreset Learning in Probabilistic Circuits
    Martin Trapp, Steven Lang, Aastha Shah, Martin Mundt, Kristian Kersting, and Arno Solin
    In The 5th Workshop on Tractable Probabilistic Modeling (UAI), 2022
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    CLEVA-Compass: A Continual Learning EValuation Assessment Compass to Promote Research Transparency and Comparability
    Martin Mundt, Steven Lang, Quentin Delfosse, and Kristian Kersting
    In International Conference on Learning Representations (ICLR), 2022
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    Elevating Perceptual Sample Quality in Probabilistic Circuits through Differentiable Sampling
    Steven Lang, Martin Mundt, Fabrizio Ventola, Robert Peharz, and Kristian Kersting
    In Proceedings of Machine Learning Research, Workshop on Preregistration in Machine Learning (NeurIPS), 2022

2021

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    DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection
    Steven Lang, Fabrizio Ventola, and Kristian Kersting
    arXiv preprint, arXiv:2109.06148, 2021

2020

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    Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits
    Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van Den Broeck, Kristian Kersting, and Zoubin Ghahramani
    In Proceedings of the 37th International Conference on Machine Learning (ICML), 2020

2019

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    WekaDeeplearning4j: A deep learning package for Weka based on Deeplearning4j
    Steven Lang, Felipe Bravo-Marquez, Christopher Beckham, Mark Hall, and Eibe Frank
    Knowledge-Based Systems, 2019