Skip to search formSkip to main contentSkip to account menu

Probabilistic soft logic

Known as: PSL 
Probabilistic soft logic (PSL) is a framework for collective, probabilistic reasoning in relational domains. PSL uses first order logic rules as a… 
Wikipedia (opens in a new tab)

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2020
2020
Probabilistic soft logic (PSL) is a statistical relational learning framework that represents complex relational models with… 
2016
2016
Lexical inference problem is a significant component of some recent core AI and NLP research problems like machine reading and… 
2016
2016
In this work, we explore a genre of puzzles ("image riddles") which involves a set of images and a question. Answering these… 
2016
2016
Markov Logic Networks (MLN) and Probabilistic Soft Logic (PSL) are widely applied formalisms in Statistical Relational Learning… 
2016
2016
Probabilistic Soft Logic has been proposed and used in several applications as an efficient way to deal with inconsistency… 
Review
2016
Review
2016
: Statistical Relational Learning (SRL) is an interdisciplinary research area that combines first­order logic and machine… 
2014
2014
We propose a new approach to semantic parsing that is not constrained by a fixed formal ontology and purely logical inference… 
Review
2013
Review
2013
Many problems in AI require dealing with both relational structure and uncertainty. As a consequence, there is a growing need for… 
2012
2012
Trust plays a key role in social interactions. Explicitly modeling trust is therefore an important aspect of social network… 
2012
2012
Annotation graphs, made available through the Linked Data initiative and Semantic Web, have significant scientific value. However…