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Tal Friedman
Tal Friedman
PhD Student, UCLA
Verified email at cs.ucla.edu - Homepage
Title
Cited by
Cited by
Year
A semantic loss function for deep learning with symbolic knowledge
J Xu, Z Zhang, T Friedman, Y Liang, G Van den Broeck
International Conference on Machine Learning, 5502-5511, 2018
2272018
PhenomeCentral: a portal for phenotypic and genotypic matchmaking of patients with rare genetic diseases
OJ Buske, M Girdea, S Dumitriu, B Gallinger, T Hartley, H Trang, ...
Human mutation 36 (10), 931-940, 2015
1162015
Approximate knowledge compilation by online collapsed importance sampling
T Friedman, G Van den Broeck
Advances in Neural Information Processing Systems, 8024-8034, 2018
172018
On Constrained Open-World Probabilistic Databases
T Friedman, GV Broeck
arXiv preprint arXiv:1902.10677, 2019
142019
Symbolic Querying of Vector Spaces: Probabilistic Databases Meets Relational Embeddings
T Friedman, G Van den Broeck
arXiv preprint arXiv:2002.10029, 2020
102020
Semantic and generalized entropy loss functions for semi-supervised deep learning
K Gajowniczek, Y Liang, T Friedman, T Ząbkowski, G Van den Broeck
Entropy 22 (3), 334, 2020
72020
Scalable Rule Learning in Probabilistic Knowledge Bases
A Jain, T Friedman, O Kuzelka, G Van den Broeck, L De Raedt
Automated Knowledge Base Construction, 2019
72019
Solving Marginal MAP Exactly by Probabilistic Circuit Transformations
YJ Choi, T Friedman, G Van den Broeck
International Conference on Artificial Intelligence and Statistics, 10196-10208, 2022
12022
Insights from the Intersection of Logic and Probabilistic Reasoning
T Friedman
University of California, Los Angeles, 2021
2021
Approximate Knowledge Compilation by Online Collapsed Importance Sampling
T Friedman, G Van den Broeck
Advances in Neural Information Processing Systems 31, 2018
2018
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