In this paper, we propose a probabilistic inference framework, called the Numerical Markov Logic Network (NMLN), to enable efficient inference of hybrid ...

Dec 31, 2020 · In this paper, we propose a probabilistic inference framework, called the Numerical Markov Logic Network (NMLN), to enable efficient inference ...

Jul 10, 2024 · In this paper, we propose a probabilistic inference framework, called the Numerical Markov Logic Network (NMLN), to enable efficient inference ...

Abstract: In recent years, the Markov Logic Network (MLN) has emerged as a powerful tool for knowledge-based inference due to its ability to combine ...

In this paper, we propose a probabilistic inference framework, called the Numerical Markov Logic Network (NMLN), to enable efficient inference of hybrid ...

Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complex- ity and uncertainty of real-world problems in ...

IEEE Intelligent Systems 36 (6), 71-79, 2021. 4, 2021. Numerical Markov logic network: A scalable probabilistic framework for hybrid knowledge inference. P ...

Markov logic networks (MLNs) have proven to be useful tools for reasoning about uncertainty in complex knowledge bases. In this paper, we extend MLNs with ...

Numerical Markov Logic Network: A Scalable Probabilistic Framework for Hybrid Knowledge Inference · Graphical models and symmetries: loopy belief propagation ...

Markov Logic Networks (MLNs) have emerged as a powerful representation that incorporates first-order logic and probabilistic graphical models.