Reviews: DeepProbLog: Neural Probabilistic Logic Programming

This work extends the ProbLog language and uses the distribution of grounded facts estimated by the ProbLog to train neural networks, which is represented as neural predicates in the ProbLog. Meanwhile, the DeepProbLog framework is able to learn ProbLog parameters and deep neural networks at the same time. The experimental results show that the DeepProbLog can perform joint probabilistic logical reasoning and neural network inference on some simple tasks. Combining perception and symbolic reasoning is an important challenge for AI and machine learning. Different to most of the existing works, this work does not make one side subsumes the other (e.g.