PhD student Rwiddhi Chakraborty at UiT
Self Supervised Explainability on Graphs
In the past decade, the availability of large-scale datasets allowed the proliferation of deep learning-based architectures in computer vision, language modelling, and graph-based data. The curation and annotation process of these datasets is overly expensive. In recent years, new methodologies emerged to train deep learning models on unlabeled data, so called self-supervision.
To prepare students on these highly relevant topics, we, University of Oslo (UiO) and UiT The Arctic University of Norway (UiT), as part of the SFI Visual Intelligence efforts, joined forces to teach a special curriculum course about bleeding edge topics related to deep learning methods based on self-supervision and non-structured data (that is, based on graphs). Moreover, due to the need to reveal the decisions made by these models, we placed special emphasis on novel techniques used to explain the inner workings of these models.
The course puts an emphasis on letting the student discuss and lead the learning endeavor. The sessions encompassed active discussions among the participants. Professors from UiO and UiT provided useful moderation and insights to the discussions. William Ho, a UiO masters’ student, mentioned, “this [course] has been the most enjoyable course I’ve ever taken [at] IFI,” due to its highly interactive setup. Also, Rwiddhi Chakraborty, from UiT, expressed the usefulness of the curriculum and discussions. Another anonymous student mentions, “[presenting papers to each other] has been fantastic to complete the learning cycle—since we are learning the content and then presenting/teaching it as well.”
The wonderful experience has already led to innovative ideas on improving collaboration between the two sites and will be integrated into future offerings of the course. After seeing the success and enthusiasm from the students, we will explore new ways of providing more joint venues for the students to collaborate between the two sites.
Responsible at UiT: Michael Kampffmeyer
Responsable at UiO: Adín Ramírez Rivera
Visual intelligence og norske forskningssentre innen kunstig intelligens er klare til å bidra til regjeringens ambisiøse milliardsatsning på KI for å utvikle trygg, pålitelig, og effektiv kunstig intelligens som vil gagne samfunnet, innovasjonen og utdanningen.
Maskinlæringsgruppa ved UiT skal i gang med å lage en permanent utstilling om kunstig intelligens. Målet er å rekruttere fremtidens forskere innen faget.
Daniel Johansen Trosten defended his PhD thesis “Improving Representation Learning for Deep Clustering and Few-shot Learning” on August 23rd 2023 at UiT The Arctic University of Norway.
Visual Intelligence researcher Kristoffer Wickstrøm was invited to give lectures at the Technical University of Denmark's summer school on self-supervised learning.
Ledig stilling som kommunikasjonsrådgiver i forskningsruppe for maskinlæring. Vi søker engasjert formidler som kan øke vår synlighet ved å formidle vår forskning til et bredt publikum.
Visual Intelligence’s advances in fundamental and applied deep learning research is gaining widespread attention and visibility.
Visual Intelligence-lead course on self-supervised learning as part of the NORA summer school 2023
The Tromsø AI Meetup 2023 brought together AI enthusiasts at Storgata Camping to connect, learn from notable speakers, and explore the exciting developments in AI, fostering a community passionate about responsible innovation in the field.
Changkyu Choi defended his PhD thesis “Advancing Deep Learning for Marine Environment Monitoring” on June 9th 2023 at UiT The Arctic University of Norway.
Visual Intelligence contributed to the Norwegian Parliament’s AI seminar organized by the Health and Care Services Committee
The University Hospital of North Norway, partner in Visual Intelligence, in the media: "AI is the path forward". Read the full story (in Norwegian).
Fjernstyrte undervannsroboter er et viktig verktøy i kartlegging, utforskning og overvåkning av verdens havområder. I slutten av april fikk 22 elever fra videregående skoler i Troms og Finnmark designe, bygge og anvende fjernstyrte undervannsroboter.
A pitch day was organized at UiT for to connect students with companies for external master’s projects and job opportunities in computer science and machine learning.
Master thesis on automation in the fish processing industry using machine learning by Josten Henriksen.
Prof. Pierre Baldi visited Visual Intelligence in Tromsø, February 16-17, 2023. The two days were filled with fruitful meetings on potential scientific collaboration between UCI and Visual Intelligence.
Machine learning phd students from Visual Intelligence present at UiT The Arctic University of Norway's open day 2023, for recruitment of new students.
VIGS is Visual Intelligence's social and scientific initiative for phd students, postdocs and early career researchers! May 3-5 VIGS will organize a joint trip to UiT's field station in Indre Troms. Sign up and read more about the social and scientific program in out event!
The Northern Lights Deep Learning Conference, Tromsø, January 9th to 13th, was a great gathering of 250 deep learning researchers.
Stine Hansen defended her PhD thesis “Leveraging Supervoxels for Medical Image Volume Segmentation With Limited Supervision” on Dec. 16th at UiT The Arctic University of Norway.
7-8 November VIGS organized a successful gathering for early career researchers in Tromsø. The program was filled with both a social and technical program and gathered around 20 researchers from the research partners in Visual Intelligence.