Nettsider med emneord «Machine Learning»

Publisert 22. okt. 2020 09:52
Bildet kan inneholde: linje.
Publisert 15. okt. 2020 14:20

How is rhythm processed in the human brain, and how can we model rhythm in machines? These are central research questions at the new RITMO Centre of Excellence.

We aim to take inspiration from rhythm in humans and other biological systems and develop models of rhythmic motion which can be applied to robotic and computing systems.

Publisert 15. okt. 2020 10:29
Bildet kan inneholde: tegnefilm, illustrasjon.
Publisert 15. okt. 2020 08:03

The Tactile Internet –a communication network that is capable of delivering real-time control, touch, and sensing/actuation information through sufficiently reliable, responsive, and intelligent connectivity – is revolutionizing the understanding of what is possible through wireless communication systems, pushing boundaries of Internet-based applications to remote physical interaction. Such remote interaction capability can be used in surgery, driving, drone-based transportation, immersive education, and adventure, etc. Although the community envisions the bright future of the tactile internet, few works implement the physical platform and specify the blockages in enabling a smooth quality of experience (QoE) during the interaction. In this project, the candidate(s) will work in a team to identify those blockages and propose the novel algorithm in network stack to enable the avatar in the real world.

Bildet kan inneholde: kjøretøy.
Publisert 15. okt. 2020 00:44

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

Publisert 18. sep. 2020 14:00
Publisert 17. sep. 2020 10:56
Publisert 11. sep. 2020 08:50
Publisert 11. sep. 2020 08:34
Bildet kan inneholde: tekst, skrift.
Publisert 9. sep. 2020 11:58

We have MSc project openings in partnership with ambitious entrepreneurs in the company VibSim AS. VibSim is a startup working on lifetime expectancy estimation for machinery, components, and vehicles by analyzing sound and vibration data.

Publisert 9. sep. 2020 10:46
Publisert 31. aug. 2020 11:45

Water flow on, in and under glaciers still remains a poorly understood system. Water can flow over the surface of glaciers, as well as through channels inside and under the ice. The water thereby has a strong influence both on ice melt and glacier dynamics, making glacial hydrology an important field of study.

Publisert 31. aug. 2020 11:42

Water flow on, in and under glaciers still remains a poorly understood system. Water can flow over the surface of glaciers, as well as through channels inside and under the ice. The water thereby has a strong influence both on ice melt and glacier dynamics, making glacial hydrology an important field of study.

Publisert 26. aug. 2020 12:59
Publisert 8. apr. 2020 09:44
Publisert 25. feb. 2020 09:17

Classification models are often used to make decisions that affect humans: whether to approve a loan application, extend a job offer, or provide insurance. In such applications, it is desirable for the individuals to not only knowing the results but also have the ability to change the decisions of the model. For example, when a person is denied a loan by a credit scoring model, in addition to know why he/she can not received the loan, it is meaningful for the person to know what he/she can do to influence the decision, i.e. what are the input variables that, if values are changed, can alter the decision of the model. Otherwise, without this information, he/she will be denied the loan as long as the model is deployed, and – more importantly – will lack agency over a decision that affects their livelihood.

Publisert 25. feb. 2020 09:15

Classification models are often used to make decisions that affect humans: whether to approve a loan application, extend a job offer, or provide insurance. In such applications, it is desirable for the individuals to not only knowing the results but also have the ability to change the decisions of the model. For example, when a person is denied a loan by a credit scoring model, in addition to know why he/she can not received the loan, it is meaningful for the person to know what he/she can do to influence the decision, i.e. what are the input variables that, if values are changed, can alter the decision of the model. Otherwise, without this information, he/she will be denied the loan as long as the model is deployed, and – more importantly – will lack agency over a decision that affects their livelihood.

Publisert 22. feb. 2020 13:00

Insights is a 4-year Marie Sklodowska-Curie Innovative Training Networks project for the career development of 12 Early Stage Researchers (ESRs) at 10 partner institutions across Europe. INSIGHTS is focused on applying the latest advances in statistics, and in particular machine learning, to particle physics.

Publisert 5. feb. 2020 17:23
Publisert 30. jan. 2020 13:28
Publisert 24. jan. 2020 13:53