Mattis Hartwig

@inproceedings{LuMoHa24,
    author    = {Malte Luttermann and Ralf Möller and Mattis Hartwig},
    title     = {{Towards Privacy-Preserving Relational Data Synthesis via Probabilistic Relational Models}},
    booktitle = {Proceedings of the Forty-Seventh German Conference on Artificial Intelligence (KI-2024)},
    year      = {2024},
    pages     = {175--189},
    publisher = {Springer},
}

@inproceedings{LuHaBrMoGe24,
  author    = {Malte Luttermann and Mattis Hartwig and Tanya Braun and Ralf Möller and Marcel Gehrke},
  title     = {Lifted Causal Inference in Relational Domains},
  booktitle = {Proceedings of the Third Conference on Causal Learning and Reasoning (CLeaR-24)},
  year      = {2024},
  volume    = {236},
  pages     = {827--842},
  publisher = {PMLR},
  url       = {https://proceedings.mlr.press/v236/luttermann24a.html},
}

@inproceedings{FroHeMoHa23,
  title     = {Evaluating the Effects of a Priori Deep Learning Image Synthesis on Multi-Modal MR-to-CT Image Registration Performance},
  author    = {Nils Frohwitter and Alessa Hering and Ralf M\"oller and Mattis Hartwig},
  year      = {2023},
  booktitle = {Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023)},
  pages     = {322-329}
}

@inproceedings{OtLeHuHa2023,
  TITLE     = {How to Think About Benchmarking Neurosymbolic AI?},
  AUTHOR    = {Johanna Ott and Arthur Ledaguenel and C{\'e}line Hudelot and Mattis Hartwig},
  URL       = {https://hal.science/hal-04136556},
  BOOKTITLE = {17th International Workshop on Neural-Symbolic Learning and Reasoning - NESY 2023},
  ADDRESS   = {Sienne, Italy},
  YEAR      = {2023},
  MONTH     = {Jul},
  KEYWORDS  = {Artificial intelligence ; Neurosymbolic},
  PDF       = {https://hal.science/hal-04136556/file/%5BNeSy%20Revised%5D%20How%20to%20Think%20About%20Benchmarking%20Neurosymbolic%20AI.pdf},
  HAL_ID    = {hal-04136556},
  HAL_VERSION = {v1},
  HAL_LOCAL_REFERENCE = {SMD}
}

@inproceedings{MenScScMoHa2023,
  TITLE     = {Improved Techniques for Training Tabular GANs Using Cramer's V Statistics},
  AUTHOR    = {Melle Mendikowski and Benjamin Schindler and Thomas Schmid and Ralf M{\"o}ller and Mattis Hartwig},
  YEAR      = {2023},
  BOOKTITLE = {Proceedings of the Canadian Conference on Artificial Intelligence},
  PAGES     = {1-12}
}

@inproceedings{WiHaKi2023,
 author       = {Alex Winter and Mattis Hartwig and Toralf Kirsten},
 title        = {Predicting Hospital Length of Stay of Patients Leaving the Emergency Department},

 year         = {2023},
 booktitle    = {Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - HEALTHINF},
 pages        = {124--131}
}

@article{HarBhPe2022,
  title={How stress can change our deepest preferences: stress habituation explained using the free energy principle},
  author={Hartwig, Mattis and Bhat, Anjali and Peters, Achim},
  journal={Frontiers in psychology},
  volume={13},
  pages={865203},
  year={2022},
  publisher={Frontiers}
}

@article{PetHarSpi2022,
  title={Obesity and Type 2 Diabetes Mellitus Explained by the Free Energy Principle},
  author={Achim Peters and Mattis Hartwig and Tobias Spiller},
  journal={Frontiers in Psychology},
  volume={13},
  pages={931701},
  year={2022},
  publisher={Frontiers}
}

@inproceedings{Stender2022, 
author={Mareike Stender and Mattis Hartwig and Tanya Braun and Ralf Möller},
title={{Increasing State Estimation Accuracy in the Inference Algorithm on a Hybrid Factor Graph Model}}, 
booktitle={The 35. International FLAIRS Conference Proceedings},  
year={2022}, 
month={May},
pages={},
publisher={},
url={https://journals.flvc.org/FLAIRS/article/view/130682}
}

@phdthesis{Hart22,
  author = {Mattis Hartwig},
  title = {{New Methods for Efficient Query Answering in Gaussian Probabilistic Graphical Models}},
  school = {University of L\"ubeck},
  year = {2022},
  month={September},
  note = {PhD thesis}
}

@inproceedings{MenHa22,
  author = {Melle Mendikowski and Mattis Hartwig}, 
  title = {{Creating Customers That Never Existed: Synthesis of E-commerce Data Using CTGAN}}, 
  booktitle = {18th International Conference on Machine Learning and Data Mining (MLDM-22)},
  address = {New York, US}, 
  year = {2022},
  date = {16.-22.07.2022},
  pages = {91--105},
  publisher = {IBAI Publishing},
  ISBN = {978-3-942952-93-4}
}

@article{HarPe21,
author={Mattis Hartwig and Achim Peters}, 
title={Cooperation and Social Rules Emerging From the Principle of Surprise Minimization},      	
journal={Frontiers in Psychology},      	
volume={11},      
pages={3668},     	
year={2021},      	  
url={https://www.frontiersin.org/article/10.3389/fpsyg.2020.606174}, 
issn={1664-1078}
}

@inproceedings{HarBrMo21,
  author = {Mattis Hartwig and Tanya Braun and Ralf M\"oller}, 
  title = {{Handling Overlaps When Lifting Gaussian Bayesian Networks}}, 
  booktitle = {Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021)},
  address = {Montreal, Kanada}, 
  year = {2021},
  date = {19.-27.08.2021},
  pages = {4228--4234},
  publisher = {IJCAI Organization},
  DOI = {https://doi.org/10.24963/ijcai.2021/581},
  ISBN = {978-0-9992411-9-6 (online)}
}

@techreport{Har20,
    Author = {Mattis Hartwig},
    Title = {{Efficient Query Answering in Nonparametric
Probabilistic Graphical Models}},
    Year = {2020},
    date = {21.-25.09.2020},
    address = {Bamberg},
    Institution = {German Conference on Artificial Intelligence (K{\"u}nstliche Intelligenz)},
    Note = {43rd German Conference on Artificial Intelligence, Doctoral Consortium}
}

@inproceedings{HaMo20b,
  author={Mattis Hartwig and Ralf Möller},
  title={How to Encode Dynamic Gaussian Bayesian Networks as Gaussian Processes?},
  booktitle = {{AI} 2020: Advances in Artificial Intelligence - 33rd Australasian Joint Conference, {AI} 2020}},
  address = { Canberra, ACT, Australia, November 29-30, 2020},
  series    = {Lecture Notes in Computer Science (LNCS)},
  volume    = {12576},
  pages     = {371--382},
  publisher = {Springer},
  doi = {https://doi.org/10.1007/978-3-030-64984-5_29}
}

@inproceedings{HarGeMo19,
  title={{Approximate Query Answering in Complex Gaussian Mixture Models}},
  author = {Mattis Hartwig and Marcel Gehrke and Ralf M\"oller}, 
booktitle = {{IEEE} International Conference on Big Knowledge, (ICBK 2019), Beijing, China, November 10-11, 2019},
  year={2019},
  pages={81--86},
  publisher = {{IEEE}},
  url       = {https://doi.org/10.1109/ICBK.2019.00019},
  publisher = {IEEE}
}