Random Sum-Product Networks: A Simple but Effective Approach to Probabilistic Deep Learning R Peharz, A Vergari, K Stelzner, A Molina, X Shao, M Trapp, K Kersting, ... UAI, 2019 | 52 | 2019 |

Spflow: An easy and extensible library for deep probabilistic learning using sum-product networks A Molina, A Vergari, K Stelzner, R Peharz, P Subramani, N Di Mauro, ... arXiv preprint arXiv:1901.03704, 2019 | 31 | 2019 |

Probabilistic deep learning using random sum-product networks R Peharz, A Vergari, K Stelzner, A Molina, M Trapp, K Kersting, ... arXiv preprint arXiv:1806.01910, 2018 | 30 | 2018 |

Faster Attend-Infer-Repeat with Tractable Probabilistic Models K Stelzner, R Peharz, K Kersting International Conference on Machine Learning, 5966-5975, 2019 | 27 | 2019 |

Structured Object-Aware Physics Prediction for Video Modeling and Planning J Kossen, K Stelzner, M Hussing, C Voelcker, K Kersting International Conference on Learning Representations, 2020 | 26 | 2020 |

Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits R Peharz, S Lang, A Vergari, K Stelzner, A Molina, M Trapp, GV Broeck, ... International Conference on Machine Learning, 2020 | 21 | 2020 |

Conditional sum-product networks: Imposing structure on deep probabilistic architectures X Shao, A Molina, A Vergari, K Stelzner, R Peharz, T Liebig, K Kersting International Conference on Probabilistic Graphical Models, 401-412, 2020 | 20 | 2020 |

Generative Adversarial Set Transformers K Stelzner, K Kersting, AR Kosiorek Workshop on Object-Oriented Learning at ICML 2020, 2020 | 4 | 2020 |

Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation K Stelzner, K Kersting, AR Kosiorek arXiv preprint arXiv:2104.01148, 2021 | 2 | 2021 |

Random Sum-Product Forests with Residual Links F Ventola, K Stelzner, A Molina, K Kersting arXiv preprint arXiv:1908.03250, 2019 | 1 | 2019 |

SP 3–Sum Product Probabilistic Programming K Stelzner, A Molina, R Peharz, A Vergari, M Trapp, I Valera, ... | | |