Probabilistic Logical Inference on the Web

By M. Alberti, Giuseppe Cota, Fabrizio Riguzzi, Riccardo Zese. 2016

17 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Natural Language Processing, Probabilistic & Bayesian Methods

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Frank D. Wood
2. Hongseok Yang
3. Jan-Willem van de Meent
4. Brooks Paige
5. Yura N. Perov
6. David Tolpin
7. Zoubin Ghahramani
8. Tom Rainforth

In Natural Language Processing

1. Frank D. Wood
2. Brooks Paige
3. Jan-Willem van de Meent
4. Hongseok Yang

In Probabilistic & Bayesian Methods

1. Frank D. Wood
2. Hongseok Yang
3. Jan-Willem van de Meent
4. Brooks Paige
5. Yura N. Perov
6. David Tolpin
7. Zoubin Ghahramani
8. Tom Rainforth

Citations in the corpus

• An Introduction to Probabilistic Programming (2018, methodology): “One link between the material presented in this tutorial and these additional languages and libraries is that the inference methodologies we will discuss apply to advanced forms of probabilistic logic programs (Alberti et al., 2016; Kimmig and De Raedt, 2017) and, in general, to the graph representa”