A Semantic Loss Function for Deep Learning with Symbolic Knowledge. - Jingyi Xu; Zilu Zhang; Tal Friedman; Yitao Liang; Guy Van den Broeck (ICML, 2018)

Approximate Knowledge Compilation by Online Collapsed Importance Sampling. - Tal Friedman; Guy Van den Broeck (NeurIPS, 2018)

On Constrained Open-World Probabilistic Databases. - Tal Friedman; Guy Van den Broeck (AKBC, 2019)

Scalable Rule Learning in Probabilistic Knowledge Bases. - Arcchit Jain; Tal Friedman; Ondrej Kuzelka; Guy Van den Broeck; Luc De Raedt (AKBC, 2019)

Symbolic Querying of Vector Spaces: Probabilistic Databases Meets Relational Embeddings. - Tal Friedman; Guy Van den Broeck (UAI, 2020)

Semantic and Generalized Entropy Loss Functions for Semi-Supervised Deep Learning. - Krzysztof Gajowniczek; Yitao Liang; Tal Friedman; Tomasz S. Zabkowski; Guy Van den Broeck (Entropy, 2020)

Solving Marginal MAP Exactly by Probabilistic Circuit Transformations. - YooJung Choi 001; Tal Friedman; Guy Van den Broeck (AISTATS, 2022)