Models, code, and papers for "Martin Vala":
Machine learning is an important research area in particle physics, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event identification and reconstruction in the 2010s. In this document we discuss promising future research and development areas in machine learning in particle physics with a roadmap for their implementation, software and hardware resource requirements, collaborative initiatives with the data science community, academia and industry, and training the particle physics community in data science. The main objective of the document is to connect and motivate these areas of research and development with the physics drivers of the High-Luminosity Large Hadron Collider and future neutrino experiments and identify the resource needs for their implementation. Additionally we identify areas where collaboration with external communities will be of great benefit.
The Swiss avalanche bulletin is produced twice a day in four languages. Due to the lack of time available for manual translation, a fully automated translation system is employed, based on a catalogue of predefined phrases and predetermined rules of how these phrases can be combined to produce sentences. The system is able to automatically translate such sentences from German into the target languages French, Italian and English without subsequent proofreading or correction. Our catalogue of phrases is limited to a small sublanguage. The reduction of daily translation costs is expected to offset the initial development costs within a few years. After being operational for two winter seasons, we assess here the quality of the produced texts based on an evaluation where participants rate real danger descriptions from both origins, the catalogue of phrases versus the manually written and translated texts. With a mean recognition rate of 55%, users can hardly distinguish between the two types of texts, and give similar ratings with respect to their language quality. Overall, the output from the catalogue system can be considered virtually equivalent to a text written by avalanche forecasters and then manually translated by professional translators. Furthermore, forecasters declared that all relevant situations were captured by the system with sufficient accuracy and within the limited time available.