Nettsider med emneord «High dimensional inference»

Economic models used for forecasting and to aid policy decisions have been estimated by the use of data from before the Covid-19 pandemic and the ensuing lockdowns, drop in economic activity and surge in unemployment. An important question for model developers and users is therefore how the empirical relationships that represented normal behavior of firms and households before Covid-19 have been affected by the pandemic and by the policy responses.

A six-year project with the goal to develop and use machine learning to improve the way social scientists can answer classic as well as emerging questions in economics that require the use of large datasets.

The adaptive immune system records all past and ongoing battles with disease and infection in the form of immune memory, stored in the form of DNA of immune receptors of adaptive immune cells. However, deciphering these signals is a grand challenge of immunology, requiring sophisticated machine learning.

Exploring the fundamental constituents of the Universe physicists are faced with very serious calculational bottlenecks. To compare new physics models to data we need to perform very computationally expensive calculations in quantum field theory (QFT).

UiO:RealArt will use artificial world data to study the real-world problem of safe medication use in pregnancy.

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.

In a wide range of applications, monitoring data streams for faults or changes in behavior (called anomalies) is of great importance.

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.

Modern science usually provides both copious amounts of data and complicated models for the part of reality it is trying to describe. Often there is even so much data, and the models so complicated, that it becomes difficult to make full use of the data in deciding which models best describe the world around us, and finding their properties. The main goal of the GAMBIT project is to develop a software tool to help physicists do just that.