Forskningsgrupper
Forskningsprosjekter
Aktive forskningsprosjekter
-
Styrke solidaritet for demokratisk enhet på tvers av grenser (SOLIDEM)
Prosjektet fokuserer på svekkende tillit og solidaritet i europeiske velferdsstater, inkludert Norge.
Avsluttede forskningsprosjekter
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Kunstig intelligens - et nytt verktøy innen assistert reproduksjonsteknologi
Prosjektet har som mål å forbedre metodene for å velge ut sædceller og embryo, og dermed øke sjansen for graviditet og levendefødte barn.
Publikasjoner og forskningsresultater
Vitenskapelige publikasjoner
Sarkhoosh, Mehdi Houshmand; Gautam, Sushant; Midoglu, Cise; Nguyen, Thu; Held, Jan; Cioppa, Anthony; Giancola, Silvio; Thambawita, Vajira;
Riegler, Michael
;
Halvorsen, Pål
(2025).
Beyond Audio: Enhancing SoccerNet-Echoes with Multimodal Event Extraction Using LLMs.
International Journal of Semantic Computing (IJSC).
https://doi.org/10.1142/s1793351x25450035
Hammer, Hugo Lewi
; Thambawita, Vajira;
Riegler, Michael
(2025).
Reply: Foundation models in IVF: from speculation to implementation with FEMI.
Human Reproduction.
Vol. 41.
https://doi.org/10.1093/humrep/deaf227
Riegler, Michael
;
Hellton, Kristoffer Herland
; Thambawita, Vajira L B;
Hammer, Hugo Lewi
(2025).
Using large language models to suggest informative prior distributions in Bayesian regression analysis.
Scientific Reports.
Vol. 15.
https://doi.org/10.1038/s41598-025-18425-9
Presacan, Oriana; Mesa, María Hernández; Aldea, Alexandru C.; Andresen, Siri; Outa, Amani al; Johannessen, Julie Aarmo; Ionescu, Bogdan; Knævelsrud, Helene;
Riegler, Michael
(2025).
Explainable AI to unveil cellular autophagy dynamics.
PLOS ONE.
Vol. 20.
https://doi.org/10.1371/journal.pone.0331045
Vikan, Magnhild
;
Aryan, Ramtin
;
Kannelønning, Mari Serine
;
Riegler, Michael
;
Danielsen, Stein Ove
(2025).
Reflecting on LLM Support in Reflexive Thematic Analysis: An Exploratory Study.
Qualitative Health Research.
https://doi.org/10.1177/10497323251365211
Sharma, Akriti; Dorobantiu, Alexandru; Ali, Saquib; Iliceto, Mario; Stensen, Mette Haug;
Delbarre, Erwan
;
Riegler, Michael
;
Hammer, Hugo Lewi
(2025).
Deep learning methods to forecasting human embryo development in time-lapse videos.
PLOS ONE.
Vol. 20.
https://doi.org/10.1371/journal.pone.0330924
Hammer, Hugo Lewi
; Thambawita, Vajira;
Riegler, Michael
(2025).
Foundation models: the next level of AI in ART.
Human Reproduction.
Vol. 40.
https://doi.org/10.1093/humrep/deaf136
Duric, Adrian; Tørresen, Jim;
Riegler, Michael
;
Hammer, Hugo Lewi
(2025).
Explanation Supported Learning: Improving Prediction Performance with Explainable Artificial Intelligence.
IEEE International Symposium on Computer-Based Medical Systems.
https://doi.org/10.1109/CBMS65348.2025.00125
Ionescu, Bogdan; Müller, Henning; Stanciu, Dan-Cristian; Andrei, Alexandra-Georgiana; Radzhabov, Ahmedkhan; Prokopchuk, Yuri; Ştefan, Liviu-Daniel; Constantin, Mihai Gabriel; Dogariu, Mihai; Kovalev, Vassili; Damm, Hendrik; Rückert, Johannes; Abacha, Asma Ben; Herrera, Alba G. Seco de; Friedrich, Christoph M.; Bloch, Louise; Brüngel, Raphael; Idrissi-Yaghir, Ahmad; Schäfer, Henning; Schmidt, Cynthia Sabrina; Pakull, Tabea M. G.; Bracke, Benjamin; Pelka, Obioma; Eryılmaz, Bahadır; Becker, Helmut; Yim, Wen-Wai; Codella, Noel; Novoa, Roberto Andres; Malvehy, Josep; Dimitrov, Dimitar; Das, Rocktim Jyoti; Xie, Zhuohan; Hee, Ming Shan; Nakov, Preslav; Koychev, Ivan; Hicks, Steven A.; Gautam, Sushant;
Riegler, Michael
; Thambawita, Vajira L B;
Halvorsen, Pål
; Fabre, Diandra; Macaire, Cécile; Lecouteux, Benjamin; Schwab, Didier; Potthast, Martin; Heinrich, Maximilian; Kiesel, Johannes; Wolter, Moritz; Anand, Sharat; Stein, Benno
(2025).
Overview of ImageCLEF 2025: Multimedia Retrieval in Medical, Social Media and Content Recommendation Applications.
Carrillo-de-Albornoz, Jorge (Red.).
Experimental IR Meets Multilinguality, Multimodality, and Interaction (CLEF 2025).. s. 290-314.
Springer Publishing Company.
https://doi.org/10.1007/978-3-032-04354-2_17
Nik, Alireza Hossein Zadeh;
Riegler, Michael
;
Halvorsen, Pål
(2025).
Impact of decoding strategies on GPU energy usage in large language model text generation.
Scientific Reports.
https://doi.org/10.1038/s41598-025-31896-0