Solving Decision Theory Problems with Probabilistic Answer Set Programming

Symbolic Parameter Learning in Probabilistic Answer Set Programming

Fast Inference for Probabilistic Answer Set Programs Via the Residual Program

A semantics for probabilistic hybrid knowledge bases with function symbols

Machine Learning Approaches for the Prediction of Gas Turbine Transients

Probabilistic Answer Set Programming with Discrete and Continuous Random Variables

Quantum algorithms for weighted constrained sampling and weighted model counting

Integration between constrained optimization and deep networks: a survey

Lifted inference for statistical statements in probabilistic answer set programming

Rapid Assessment of COVID-19 Mortality Risk with GASS Classifiers

Symbolic DNN-Tuner

Probabilistic Logic Models for the Lightning Network

Prediction of Gas Turbine Trip: A Novel Methodology Based on Random Forest Models

A Machine Learning Framework for Multi-Hazard Risk Assessment at the Regional Scale in Earthquake and Flood-Prone Areas

Symbolic DNN-Tuner: A Python and ProbLog-based system for optimizing Deep Neural Networks hyperparameters

Abduction with probabilistic logic programming under the distribution semantics

A semantics for Hybrid Probabilistic Logic programs with function symbols

Probabilistic inductive constraint logic

Identification of natural selection in genomic data with deep convolutional neural network

Nonground Abductive Logic Programming with Probabilistic Integrity Constraints