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Ten selected Publications

  • De Raedt L, Kersting K, Natarajan S, & Poole D (2016).
    Statistical Relational Artificial Intelligence: Logic, Probability and Computation.
    Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan Claypool Publishers, 1-198.
    DOI: 10.1007/978-3-031-01574-8 

  • Friedrich F, Stammer W, Schramowski P, & Kersting K1,4,5 (2023).
    A typology for exploring the mitigation of shortcut behaviour.
    Nature Machine Intelligence, 5:319-330.
    DOI: 10.1038/s42256-023-00612-w 

  • Guy Van den Broeck, Kristian Kersting, Sriraam Natarajan, David Poole (eds.) (2021):
    “An Introduction to Lifted Probabilistic Inference”.
    Neural Information Processing series, MIT Press, ISBN: 9780262542593.
    DOI: 10.7551/mitpress/10548.001.0001 

  • Kersting K, Mladenov M, & Tokmakov P (2017).
    Relational linear programming.
    Artificial Intelligence Journal (AIJ), 244:188-216.
    DOI: 10.1016/j.artint.2015.06.009 

  • Peharz R, Lang S, Vergari A, Stelzner K, Molina A, Trapp M, Van den Broeck G, Kersting K, & Ghahramani Z (2020).
    Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits.
    International Conference on Machine Learning (ICML).
    URL: http://proceedings.mlr.press/v119/peharz20a/peharz20a.pdf

  • Ramanan N, Kunapuli G, Khot T, Fatemi B, Kazemi SM, Poole D, Kersting K, & Natarajan S (2021).
    Structure learning for relational logistic regression: an ensemble approach.
    Data Minining and Knowledge Discovery (DAMI), 35(5), 2089-2111.
    DOI: 10.1007/s10618-021-00770-8 

  • Schramowski P, Turan C, Andersen N, Rothkopf CA, & Kersting K (2022):
    Large pre-trained language models contain human-like biases of what is right and wrong to do.
    Nature Machine Intelligence, 4, 258-268.
    DOI: 10.1038/s42256-022-00458-8
     
  • Shindo H, Pfanschilling V, Dahmi DS, & Kersting K (2023).
    alphaILP: Thinking Visual Scenes as Differentiable Logic Programs.
    Machine Learning Journal.
    DOI: 10.1007/s10994-023-06320-1 

  • Zamani Z, Sanner S, Poupart P, & Kersting K (2012).
    Symbolic dynamic programming for continuous state and observation POMDPs.
    Conference on Neural Information Processing Systems (NeurIPS).
    URL: https://papers.nips.cc/paper_files/paper/2012

  • Zecevic M, Dhami DS, Karanam A, Natarajan S, & Kersting K (2021):
    Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models.
    Conference on Neural Information Processing Systems (NeurIPS), 15019-15031.
    URL: https://papers.nips.cc/paper_files/paper/2021

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