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Qinghua Liu; Andrew Henry Reiner; Arnoldo Frigessi Di Rattalma; Ida Scheel; Diverse personalized recommendations with uncertainty from implicit preference data with the Bayesian Mallows model Knowledge-Based Systems, pp. 1 12 , doi: https://doi.org/10.1016/j.knosys.2019.104960 , 2019. Scientific article

Xavier Tekpli; Tonje Gulbrandsen Lien; Andreas Hagen Røssevold; Daniel J.H. Nebdal; Elin Borgen; et al. An independent poor-prognosis subtype of breast cancer defined by a distinct tumor immune microenvironment Nature Communications, pp. 1 14 , doi: https://doi.org/10.1038/s41467-019-13329-5 , 2019. Scientific article

Publisher Springer Nature

Dag Bjarne Tjøstheim; Discussion of Models as Approximations I & II Statistical Science, pp. 575 579 , doi: https://doi.org/10.1214/19-STS725 , 2019. Scientific article

Håkon Otneim; Dag Bjarne Tjøstheim; Measuring conditional dependence using the local Gaussian partial correlation 2019. Lecture

Jonas Moss; Martin Tveten; kdensity: An R package for kernel density estimation with parametric starts and asymmetric kernels Journal of Open Source Software (JOSS), doi: https://doi.org/10.21105/joss.01566 , 2019. Scientific article

Martin Tveten; Å studere matematikk ved UiO 2019. Lecture popular

Marie Lilleborge; Ragnhild Sørum Falk; Hege Elisabeth Giercksky Russnes; Torill Sauer; Giske Ursin; et al. Risk of breast cancer by prior screening results among women participating in BreastScreen Norway Cancer, pp. 3330 3337 , doi: https://doi.org/10.1002/cncr.32330 , 2019. Scientific article

Publisher John Wiley & Sons

Marie Lilleborge; Analyser av kvinners screeninghistorikk: Hvem får brystkreft? 2019. Scientific lecture

Yujia Zhang; Michael C. Kampffmeyer; Xiaoguang Zhao; Min Tan; Deep Reinforcement Learning for Query-Conditioned Video Summarization Applied Sciences, pp. 1 16 , doi: https://doi.org/10.3390/app9040750 , 2019. Scientific article

Publisher MDPI

Michael C. Kampffmeyer; Yinbo Chen; Xiaodan Liang; Hao Wang; Yujia Zhang; et al. Rethinking knowledge graph propagation for zero-shot learning Computer Vision and Pattern Recognition, pp. 11479 11488 , doi: https://doi.org/10.1109/CVPR.2019.01175 , 2019. Scientific article

Publisher IEEE conference proceedings

Daniel Johansen Trosten; Andreas Storvik Strauman; Michael C. Kampffmeyer; Robert Jenssen; Recurrent Deep Divergence-based Clustering for Simultaneous Feature Learning and Clustering of Variable Length Time Series Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 3257 3261 , doi: https://doi.org/10.1109/ICASSP.2019.8682365 , 2019. Scientific article

Publisher IEEE (Institute of Electrical and Electronics Engineers)

Kristoffer Knutsen Wickstrøm; Michael C. Kampffmeyer; Robert Jenssen; Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps Medical Image Analysis, doi: https://doi.org/10.1016/j.media.2019.101619 , 2019. Scientific article

Yujia Zhang; Michael C. Kampffmeyer; Xiaodan Liang; Dingwen Zhang; Min Tan; et al. Dilated temporal relational adversarial network for generic video summarization Multimedia Tools and Applications, pp. 35237 35261 , doi: https://doi.org/10.1007/s11042-019-08175-y , 2019. Scientific article

Publisher Springer

Torgeir Brenn; Lars-Petter Gjøvik; Gunnar Ljosdahl Rasmussen; Tony Bauna; Michael Kampffmeyer; et al. Operationalizing Ship Detection Using Deep Learning , 2019. Scientific lecture

Solveig Engebretsen; Ingrid Kristine Glad; Additive monotone regression in high and lower dimensions Statistics Surveys, pp. 1 51 , doi: https://doi.org/10.1214/19-SS124 , 2019. Scientific article