• Arthur Colombini Gusmão. Interpreting Embedding Models of Knowledge Bases. (Master’s thesis) Universidade de São Paulo, 2018. Link.
  • Francisco H.O. Vieira de Faria, Arthur Colombini Gusmão, Glauber De Bona, Denis Deratani Mauá, Fabio Gagliardi Cozman. Speeding Up Parameter and Rule Learning for Acyclic Probabilistic Logic Programs. International Journal of Approximate Reasoning, vol. 106, pp. 32-50, 2019. Link.
  • Arthur Colombini Gusmão, Alvaro Henrique Chaim Correia, Glauber De Bona, and Fabio Gagliardi Cozman. Interpreting Embedding Models of Knowledge Bases: A Pedagogical Approach. Proceedings of the ICML Workshop on Human Interpretability in Machine Learning, pp. 79-86, 2018. Link. Slides. Presentation.
  • Francisco H. O. Vieira de Faria, Arthur C. Gusmao, Glauber De Bona, Denis D. Maua, and Fabio G. Cozman. Parameter Learning in ProbLog with Probabilistic Rules. Symposium on Knowledge Discovery, Mining and Learning (KDMILE), pp. 27-34, 2017. Preprint link.
  • Francisco H. O. Vieira de Faria, Arthur C. Gusmao, Fabio G. Cozman, and Denis D. Maua. Speeding-up ProbLog’s Parameter Learning (Extended Abstract). International Workshop on Statistical Relational AI (StarAI), 2017. Link.