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ORCIDKarl Stelzner
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2020 – today
- 2023
[b1]Karl Stelzner:
Elements of Unsupervised Scene Understanding: Objectives, Structures, and Modalities. Technical University of Darmstadt, Germany, 2023- 2022
- [j1]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: 298-313 (2022) - [i8]Xiaoting Shao, Karl Stelzner, Kristian Kersting:
Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement. CoRR abs/2202.00391 (2022) - 2021
- [i7]Karl Stelzner, Kristian Kersting, Adam R. Kosiorek:
Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation. CoRR abs/2104.01148 (2021) - 2020
- [c6]Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting:
Structured Object-Aware Physics Prediction for Video Modeling and Planning. ICLR 2020 - [c5]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: 7563-7574 - [c4]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: 401-412 - [c3]Fabrizio Ventola, Karl Stelzner, Alejandro Molina, Kristian Kersting:
Residual Sum-Product Networks. PGM 2020: 545-556 - [i6]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 abs/2004.06231 (2020)
2010 – 2019
- 2019
- [c2]Karl Stelzner, Robert Peharz, Kristian Kersting:
Faster Attend-Infer-Repeat with Tractable Probabilistic Models. ICML 2019: 5966-5975 - [c1]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: 334-344 - [i5]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 abs/1901.03704 (2019) - [i4]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 abs/1905.08550 (2019) - [i3]Fabrizio Ventola, Karl Stelzner, Alejandro Molina, Kristian Kersting:
Random Sum-Product Forests with Residual Links. CoRR abs/1908.03250 (2019) - [i2]Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting:
Structured Object-Aware Physics Prediction for Video Modeling and Planning. CoRR abs/1910.02425 (2019) - 2018
- [i1]Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Kristian Kersting, Zoubin Ghahramani:
Probabilistic Deep Learning using Random Sum-Product Networks. CoRR abs/1806.01910 (2018)
Coauthor Index
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