Karl Stelzner

Publication Activity (10 Years)

Years Active: 2018-2022
Publications (10 Years): 15

Top Topics

Generative Model

Top Venues

Int. J. Approx. Reason.

Publications

Xiaoting Shao, Karl Stelzner, Kristian Kersting
Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement. CoRR (2022)
Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting
Conditional sum-product networks: Modular probabilistic circuits via gate functions. Int. J. Approx. Reason. 140 (2022)
Karl Stelzner, Kristian Kersting, Adam R. Kosiorek
Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation. CoRR (2021)
Fabrizio Ventola, Karl Stelzner, Alejandro Molina, Kristian Kersting
Residual Sum-Product Networks. PGM (2020)
Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. CoRR (2020)
Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. PGM (2020)
Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. ICML (2020)
Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting
Structured Object-Aware Physics Prediction for Video Modeling and Planning. ICLR (2020)
Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting
Structured Object-Aware Physics Prediction for Video Modeling and Planning. CoRR (2019)
Karl Stelzner, Robert Peharz, Kristian Kersting
Faster Attend-Infer-Repeat with Tractable Probabilistic Models. ICML (2019)
Fabrizio Ventola, Karl Stelzner, Alejandro Molina, Kristian Kersting
Random Sum-Product Forests with Residual Links. CoRR (2019)
Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Xiaoting Shao, Kristian Kersting, Zoubin Ghahramani
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning. UAI (2019)
Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. CoRR (2019)
Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Pranav Subramani, Nicola Di Mauro, Pascal Poupart, Kristian Kersting
SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks. CoRR (2019)
Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Kristian Kersting, Zoubin Ghahramani
Probabilistic Deep Learning using Random Sum-Product Networks. CoRR (2018)