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Guy Van den Broeck
Guy Van den Broeck
Professor and Samueli Fellow, UCLA
Geverifieerd e-mailadres voor cs.ucla.edu - Homepage
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A semantic loss function for deep learning with symbolic knowledge
J Xu, Z Zhang, T Friedman, Y Liang, G Van den Broeck
ICML, 2018
5342018
Inference and learning in probabilistic logic programs using weighted Boolean formulas
D Fierens, G Van den Broeck, J Renkens, D Shterionov, B Gutmann, ...
Theory and Practice of Logic Programming, 2013
4302013
Lifted probabilistic inference by first-order knowledge compilation
G Van den Broeck, N Taghipour, W Meert, J Davis, L De Raedt
International Joint Conference on Artificial Intelligence (IJCAI), 2011
2372011
On the tractability of SHAP explanations
G Van den Broeck, A Lykov, M Schleich, D Suciu
Journal of Artificial Intelligence Research 74, 851-886, 2022
2022022
Probabilistic sentential decision diagrams
D Kisa, G Van den Broeck, A Choi, A Darwiche
Fourteenth International Conference on the Principles of Knowledge …, 2014
1982014
Probabilistic inference in hybrid domains by weighted model integration
V Belle, A Passerini, G Van den Broeck
Proceedings of 24th International Joint Conference on Artificial …, 2015
1292015
On the completeness of first-order knowledge compilation for lifted probabilistic inference
G Van den Broeck
Annual Conference on Neural Information Processing Systems (NeurIPS), 2011
124*2011
Skolemization for Weighted First-Order Model Counting
G Van den Broeck, W Meert, A Darwiche
Proceedings of the 14th International Conference on Principles of Knowledge …, 2013
1192013
Learning the structure of probabilistic sentential decision diagrams
Y Liang, J Bekker, G Van den Broeck
Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence …, 2017
1102017
Probabilistic circuits: A unifying framework for tractable probabilistic models
Y Choi, A Vergari, G Van den Broeck
UCLA. URL: http://starai. cs. ucla. edu/papers/ProbCirc20. pdf, 6, 2020
1062020
Inference in probabilistic logic programs using weighted CNF's
D Fierens, G Van den Broeck, I Thon, B Gutmann, L De Raedt
Proceedings of the 27th Conference on Uncertainty in Artificial Intelligence …, 2011
1062011
Monte-Carlo tree search in poker using expected reward distributions
G Van den Broeck, K Driessens, J Ramon
Advances in Machine Learning, 367-381, 2009
1032009
Scaling exact inference for discrete probabilistic programs
S Holtzen, G Van den Broeck, T Millstein
Proceedings of the ACM on Programming Languages 4 (OOPSLA), 1-31, 2020
102*2020
Inducing probabilistic relational rules from probabilistic examples
L De Raedt, A Dries, I Thon, G Van den Broeck, M Verbeke
Twenty-fourth international joint conference on artificial intelligence, 2015
972015
Algebraic model counting
A Kimmig, G Van den Broeck, L De Raedt
Journal of Applied Logic 22, 46-62, 2017
95*2017
On the paradox of learning to reason from data
H Zhang, LH Li, T Meng, KW Chang, GV Broeck
arXiv preprint arXiv:2205.11502, 2022
912022
Tractability through Exchangeability: A New Perspective on Efficient Probabilistic Inference
M Niepert, G Van den Broeck
AAAI Conference on Artificial Intelligence, 2014
902014
An algebraic Prolog for reasoning about possible worlds
A Kimmig, G Van den Broeck, L De Raedt
AAAI Conference on Artificial Intelligence., 2011
882011
DTProbLog: A decision-theoretic probabilistic Prolog
G Van den Broeck, I Thon, M van Otterlo, L De Raedt
AAAI conference on artificial intelligence (AAAI 2010), 2010
872010
Lifted Inference and Learning in Statistical Relational Models
G Van den Broeck
KU Leuven, 2013
832013
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Artikelen 1–20