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Karl Stelzner
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Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement


Feb 01, 2022
Xiaoting Shao, Karl Stelzner, Kristian Kersting

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Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation


Apr 02, 2021
Karl Stelzner, Kristian Kersting, Adam R. Kosiorek

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* 15 pages, 3 figures. For project page with videos, see http://stelzner.github.io/obsurf/ 
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Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits


Apr 13, 2020
Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani

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Structured Object-Aware Physics Prediction for Video Modeling and Planning


Oct 06, 2019
Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting

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Random Sum-Product Forests with Residual Links


Aug 08, 2019
Fabrizio Ventola, Karl Stelzner, Alejandro Molina, Kristian Kersting

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Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures


May 21, 2019
Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting

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* 13 pages, 6 figures 
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SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks


Jan 11, 2019
Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Pranav Subramani, Nicola Di Mauro, Pascal Poupart, Kristian Kersting

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* 4 pages, 1 figure, code 
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Probabilistic Deep Learning using Random Sum-Product Networks


Jun 22, 2018
Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Kristian Kersting, Zoubin Ghahramani

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