Abstract: Particle filtering is a sequential Monte Carlo simulation based on nonlinear filtering algorithm. The method may cope with any nonlinear and non-Gaussian ...

The biggest limitation of particle filters is that for a large amount of particles, CPU implementation is incredibly costly. To compensate for this, historically SLAM algorithms relied heavily on good ...

There was an error while loading. Please reload this page. This repo describes in detail the theoretical foundations and practical implementation of the particle ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...

An innovative algorithm for detecting collisions of high-speed particles within nuclear fusion reactors has been developed, inspired by technologies used to determine whether bullets hit targets in ...