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Zehn ausgewählte Publikationen

• Thomas T, Straub D, Tatai F, Shene M, Tosik T, Kersting K, Rothkopf C (2024).
  Modeling dataset bias in machine-learned theories of economic decision making.
  Nature Human Behaviour, 8, 679-691.
  DOI: 10.1038/s41562-023-01784-6
  
  
• Friedrich F, Stammer W, Schramowski P, & Kersting K (2023). 
  A typology for exploring the mitigation of shortcut behaviour.
  Nature Machine Intelligence, 5:319-330. 
  DOI: 10.1038/s42256-023-00612-w 
  
  
• Yu Z, Trapp M, Kersting K (2023). 
  Characteristic Circuits.
  Advances in Neural Information Processing Systems 36 (NeurIPS 2023).
  URL: https://openreview.net/forum?id=5W7cXno10k 
  
  
• Brack M, Schramowski P, Deiseroth B, Kersting K (2023).
  ILLUME: Rationalizing Vision-Language Models through Human Interactions.
  Proceedings of the 40th International Conference on Machine Learning (ICML).
  URL: https://openreview.net/pdf?id=5e5ozhz2jF 
  
  
• 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 
  
  
• 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 
  
  
• Zecevic M, Dhami DS, Karanam A, Natarajan S, Kersting K (2021).
  Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models.
  Advances in Neural Information Processing Systems 34 (NeurIPS 2021), 15019-15031.
  URL:https://proceedings.neurips.cc/paper/2021/file/7eb7eabbe9bd03c2fc99881d04da9cbd-Paper.pdf 
  
  
• 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 
  
  
• 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