Nettsider med emneord «Machine Learning»

This paper by Sigurd Holmsen et al. has been accepted at NeurIPS 2026. We introduce a non-parametric mutual information estimator that uses vine copulas to offer fast, interpretable, and accurate estimates.

Urban flooding caused by intense rainfall has been an increasing challenge for cities and communities in the world. More frequent and intense extreme weather events can lead to rapid urban surface flooding, combined with flooding from the sewer systems and from the rivers, which can cause significant damage to infrastructure and property, also threatening human safety.

Signe Riemer-Sørensen, Research Manager at SINTEF.

 A molecular dynamics study with machine learning potentials. The influence of the organic residue and the solvent in the Schlenk equilibrium for Grignard reagents in THF.In this paper we study the behaviour of different Grignard reagents in organic solution with a newly developed machine learning interatomic potential.

The use of deep learning to detect and characterise histopathological images is anticipated to substantially enhance current clinical practice through more efficient and objective evaluation of diseases and more personalised treatment for the individual patient. Interested students are encourage to reach out to discuss current possibilities in the longstanding collaboration between the DSB group and the Institute for Cancer Genetics and Informatics at Oslo University Hospital.

Oppgaven utføres i samarbeid med Forsvarets forskningsinstitutt (FFI) på Kjeller.