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ProbLog: A Probabilistic Prolog and Its Application in Link Discovery
We introduce ProbLog, a probabilistic extension of Prolog. A ProbLog program defines a distribution over logic programs by specifying for each clause the probability that it belongs to a randomlyExpand
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A short introduction to probabilistic soft logic
TLDR
This paper provides an overview of the PSL language and its techniques for inference and weight learning. Expand
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On the implementation of the probabilistic logic programming language ProbLog
TLDR
We introduce algorithms that allow the efficient execution of these queries, discuss their implementation on top of the YAP-Prolog system and evaluate their performance in the context of large networks of biological entities. Expand
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Probabilistic (logic) programming concepts
TLDR
A multitude of different probabilistic programming languages exists today, all extending a traditional programming language with primitives to support modeling of complex, structured probability distributions. Expand
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DeepProbLog: Neural Probabilistic Logic Programming
TLDR
We introduce DeepProbLog, a probabilistic logic programming language that incorporates deep learning by means of neural predicates. Expand
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Parameter Learning in Probabilistic Databases: A Least Squares Approach
TLDR
We introduce the problem of learning the parameters of the probabilistic database ProbLog. Expand
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Parameter estimation in ProbLog from annotated queries
TLDR
We introduce the problem of learning the parameters of the probabilistic database ProbLog. Expand
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On the Efficient Execution of ProbLog Programs
TLDR
We present exact and approximate inference algorithms for ProbLog, a recent probabilistic extension of Prolog motivated by the mining of large biological networks. Expand
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Susceptibility of multidrug-resistant human leukemia cell lines to human interleukin 2-activated killer cells.
Considering the possibility to overcome drug resistance by other treatment strategies than chemotherapy we investigated the susceptibility of three independently selected multidrug-resistant sublinesExpand
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Towards digesting the alphabet-soup of statistical relational learning
TLDR
This paper reports on our work towards the development of a probabilistic logic programming environment intended as a target language in which other Probabilistic languages can be compiled, thereby contributing to the digestion of the “alphabet soup”. Expand
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