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Tractable Computation of Expected Kernels by Circuits


Feb 21, 2021
Wenzhe Li, Zhe Zeng, Antonio Vergari, Guy Van den Broeck


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A Compositional Atlas of Tractable Circuit Operations: From Simple Transformations to Complex Information-Theoretic Queries


Feb 11, 2021
Antonio Vergari, YooJung Choi, Anji Liu, Stefano Teso, Guy Van den Broeck


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An Empirical Study on the Generalization Power of Neural Representations Learned via Visual Guessing Games


Jan 31, 2021
Alessandro Suglia, Yonatan Bisk, Ioannis Konstas, Antonio Vergari, Emanuele Bastianelli, Andrea Vanzo, Oliver Lemon

* Accepted paper for the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021) 

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Imagining Grounded Conceptual Representations from Perceptual Information in Situated Guessing Games


Nov 05, 2020
Alessandro Suglia, Antonio Vergari, Ioannis Konstas, Yonatan Bisk, Emanuele Bastianelli, Andrea Vanzo, Oliver Lemon

* Accepted to the International Conference on Computational Linguistics (COLING) 2020 

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Strudel: Learning Structured-Decomposable Probabilistic Circuits


Jul 18, 2020
Meihua Dang, Antonio Vergari, Guy Van den Broeck

* 13 pages, 9 figures, to be published on PGM2020 (The 10th International Conference on Probabilistic Graphical Models) 

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Handling Missing Data in Decision Trees: A Probabilistic Approach


Jun 29, 2020
Pasha Khosravi, Antonio Vergari, YooJung Choi, Yitao Liang, Guy Van den Broeck


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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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Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing


Feb 28, 2020
Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck


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On Tractable Computation of Expected Predictions


Oct 31, 2019
Pasha Khosravi, YooJung Choi, Yitao Liang, Antonio Vergari, Guy Van den Broeck


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Hybrid Probabilistic Inference with Logical Constraints: Tractability and Message Passing


Sep 30, 2019
Zhe Zeng, Fanqi Yan, Paolo Morettin, Antonio Vergari, Guy Van den Broeck


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Hybrid Probabilistic Inference with Logical Constraints: Tractability and Message-Passing


Sep 20, 2019
Zhe Zeng, Fanqi Yan, Paolo Morettin, Antonio Vergari, Guy Van den Broeck


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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

* 13 pages, 6 figures 

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From Variational to Deterministic Autoencoders


Apr 01, 2019
Partha Ghosh, Mehdi S. M. Sajjadi, Antonio Vergari, Michael Black, Bernhard Schölkopf

* Partha Ghosh and Mehdi S. M. Sajjadi contributed equally to this work 

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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

* 4 pages, 1 figure, code 

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Automatic Bayesian Density Analysis


Oct 03, 2018
Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera


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Visualizing and Understanding Sum-Product Networks


Aug 24, 2018
Antonio Vergari, Nicola Di Mauro, Floriana Esposito

* Machine Learning Journal paper (First Online), 24 pages 

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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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Sum-Product Networks for Hybrid Domains


Nov 06, 2017
Alejandro Molina, Antonio Vergari, Nicola Di Mauro, Sriraam Natarajan, Floriana Esposito, Kristian Kersting

* 16 Pages, 5 Figures 

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Towards Representation Learning with Tractable Probabilistic Models


Aug 08, 2016
Antonio Vergari, Nicola Di Mauro, Floriana Esposito

* 10 pages, submitted to ECML-PKDD 2016 Doctoral Consortium 

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