Nettsider med emneord «Boosting»

The objective of StREP is to provide a comprehensive and unified account of the decision to request public votes and the consequences thereof for observed behaviour.

A primary goal of the Oman Drilling Project’s Multi-Borehole Observatory has been to understand geo-chemical/physical changes in the rock fluid environment that can be used to store human generated CO2. These boreholes have produced dozens of terabytes of seismic, hydrologic, geologic, and rock mechanics data.

The recent summer drought events in Europe and their associated devastating wildfires highlight the importance of understanding and predicting such extreme events and their impact.

In MASSIVE, the project team aims at improving glacier mapping and surface glacier mass balance estimation techniques with the help of machine learning, especially deep learning. We will develop the methodology for glaciers in Norway, Svalbard, the European Alps and the Himalayas and then expand it to regions with different glacier characteristics.

For maritime safety surveillance we develop new approaches
based on the availability of large arrays of sensors, which
monitor condition and performance of vessels, machinery, or
power systems.

BigInsight produces innovative solutions for key data-driven challenges facing our consortium of private, public and research partners, by developing original statistical and machine learning methodologies.

We develop and apply methods based on machine learning for chemistry and materials science. At the method level, our focus is on data (datasets computed with quantum mechanics methods), representations (graphs based on electronic structure theory), and models (graph neural networks and boosted trees).