Probabilistic Deep Learning using Random Sum-Product Networks. - Robert Peharz; Antonio Vergari; Karl Stelzner; Alejandro Molina 001; Martin Trapp 001; Kristian Kersting; Zoubin Ghahramani (CoRR, 2018)

Faster Attend-Infer-Repeat with Tractable Probabilistic Models. - Karl Stelzner; Robert Peharz; Kristian Kersting (ICML, 2019)

Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning. - Robert Peharz; Antonio Vergari; Karl Stelzner; Alejandro Molina 001; Martin Trapp 001; Xiaoting Shao; Kristian Kersting; Zoubin Ghahramani (UAI, 2019)

SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks. - Alejandro Molina 001; Antonio Vergari; Karl Stelzner; Robert Peharz; Pranav Subramani; Nicola Di Mauro; Pascal Poupart; Kristian Kersting (CoRR, 2019)

Random Sum-Product Forests with Residual Links. - Fabrizio Ventola; Karl Stelzner; Alejandro Molina 001; Kristian Kersting (CoRR, 2019)

Structured Object-Aware Physics Prediction for Video Modeling and Planning. - Jannik Kossen; Karl Stelzner; Marcel Hussing; Claas Voelcker; Kristian Kersting (ICLR, 2020)

Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. - Robert Peharz; Steven Lang; Antonio Vergari; Karl Stelzner; Alejandro Molina 001; Martin Trapp 001; Guy Van den Broeck; Kristian Kersting; Zoubin Ghahramani (ICML, 2020)

Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. - Xiaoting Shao; Alejandro Molina 001; Antonio Vergari; Karl Stelzner; Robert Peharz; Thomas Liebig; Kristian Kersting (PGM, 2020)

Residual Sum-Product Networks. - Fabrizio Ventola; Karl Stelzner; Alejandro Molina 001; Kristian Kersting (PGM, 2020)

Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation. - Karl Stelzner; Kristian Kersting; Adam R. Kosiorek (CoRR, 2021)

Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement. - Xiaoting Shao; Karl Stelzner; Kristian Kersting (CoRR, 2022)

Conditional sum-product networks: Modular probabilistic circuits via gate functions. - Xiaoting Shao; Alejandro Molina 001; Antonio Vergari; Karl Stelzner; Robert Peharz; Thomas Liebig; Kristian Kersting (Int. J. Approx. Reason., 2022)

Elements of Unsupervised Scene Understanding: Objectives, Structures, and Modalities. - Karl Stelzner (2023)