Recently, some works have suggested methods to combine variational probabilistic inference with Monte Carlo sampling. One promising approach is via local optimal transport. In this approach, a gradient steepest descent ...

We propose a fast classifier that is able to predict atrial fibrillation inducibility in patient-specific cardiac models. Our classifier is general and it does not require re-training for new anatomies, fibrosis patterns, ...

In this work, a novel sequential Monte Carlo filter is introduced which aims at an efficient sampling of the state space. Particles are pushed forward from the prediction to the posterior density using a sequence of mappings ...

The problems that can be solved through the machine learning approach also have influence on particularities of the implemented algorithms, they are divided in three large groups: regression, classification and clustering. ...

Road accidents occur all over the world and end up being a concern to be faced continuously by society and transport safety professionals. The reduction of the number of road accidents is a challenge to society and ...

In the pattern recognition research field, Support Vector Machines (SVM) have been an effectiveness tool for classification purposes, being successively employed in many applications. The SVM input data is transformed into ...