The research problem of this paper is interesting and meaningful. The paper present a novel family of relational machine learning models. However, it would be better if some flaws of the paper can be modified. In line 20, the paper write "We aim to advance the .. models which learn efficient and effective cs". What are the shortcomings of existing methods in terms of efficiency and representation?

"Until now, machine learning has neglected a full integration of causality, and this paper argues that it would indeed benefit from integrating causal concepts." This article was originally published by Ben Dickson on TechTalks, a publication that examines trends in technology, how they affect the way we live and do business, and the problems they solve. But we also discuss the evil side of technology, the darker implications of new tech and what we need to look out for. You can read the original article here.

"Until now, machine learning has neglected a full integration of causality, and this paper argues that it would indeed benefit from integrating causal concepts." Ben Dickson is a software engineer and the founder of TechTalks. He writes about technology, business, and politics. This story originally appeared on Bdtechtalks.com.

Until now, machine learning has neglected a full integration of causality, and this paper argues that it would indeed benefit from integrating causal concepts.