Complex Systems Modeling

PUBLICATIONS for 2012 - 2023 (in progress)

2023

Aksamit, N. O., Hartmann, R., Lohse, D., & Haller, G. (2023). Interplay between advective, diffusive and active barriers in (rotating) Rayleigh-Bénard flow. Journal of Fluid Mechanics, 969, A27. https://doi.org/10.1017/jfm.2023.563
Aksamit, N. O., Scharian, R. K., Hutchings, L. K., & Lukovich, J. V. (2023). A quasi-objective single buoy approach for understanding Lagrangian coherent structures and sea ice dynamics. The Cryosphere, 17, 1545-156. https://doi.org/10.5194/tc-17-1545-2023
Bianchi, F. M. (2023). Simplifying clustering with graph neural networks. In Proceedings of the Northern Lights Deep Learning Workshop 2023, 4. https://doi.org/10.7557/18.6790
Bianchi, F. M. & Lachi, V. (2023). The expressive power of pooling in graph neural networks. Advances in Neural Information Processing Systems, 37. https://doi.org/10.48550/arXiv.2304.01575
Bochow, N., Poltronieri, A., Robinson, A., Montoya, M., Rypdal, M. W., & Boers, N. (2023). Overshooting the critical threshold for the Greenland ice sheet. Nature, 622, 528-536. https://doi.org/10.1038/s41586-023-06503-9
Cini, A., Marisca, I., Bianchi, F. M., & Alippi, C. (2023). Scalable spatiotemporal graph neural networks. In Proceedings of the AAAI conference on artificial intelligence, 37(6), 7218-7226. https://doi.org/10.1609/aaai.v37i6.25880
Eikeland, O. F., Kelsall, C. C., Buznitsky, K., Verma, S., Bianchi, F. M., Chiesa, M., & Henry, A. (2023). Power availability of PV plus thermal batteries in real-world electric power grids. Applied Energy, 348, 121572. https://doi.org/10.1016/j.apenergy.2023.121572
Espinasse, M., Mikkelsen, E., Sørbye, S. H., Skern-Mauritzen, M., Falk-Andersson, J., & Fauchald, P. (2023). Seafood production in northern Norway: Analyzing variation and co-development in aquaculture and coastal fisheries. Marine Policy, 155, 10577. https://doi.org/10.1016/j.marpol.2023.105777
Guerra, M., Bianchi, F. M., Scardapane, S., & Spinelli, I. (2023). Explainability in subgraphs-enhanced Graph Neural Networks. In Proceedings of the Northern Lights Deep Learning Workshop 2023, 4. https://doi.org/10.7557/18.6796
Guerra, M., Scardapane, S., & Bianchi, F. M. (2023). Probabilistic load forecasting with Reservoir Computing. IEEE Access, 11, 145989 - 146002. https://doi.org/10.1109/ACCESS.2023.3343467
Hansen, J. B. & Bianchi, F. M. (2023). Total variation graph neural networks. Proceedings of Machine Learning Research, 202, 12445-12468. https://proceedings.mlr.press/v202/hansen23a.html
Kočiščák, S., Kvammen, A., Mann, I., Sørbye, S. H., Theodorsen, A., & Zaslavsky, A. (2023). Modelling solar orbiter dust detection rates in inner heliosphere as a Poisson process. Astronomy and Astrophysics, 670, A140. https://doi.org/10.1051/0004-6361/202245165
Korzeniowska, M. A., Theodorsen, A., Rypdal, M. W., & Garcia, O. E. (2023). Apparent universality of 1/f spectra as an artifact of finite-size effects. Physical Review Research, 5, L022066. https://doi.org/10.1103/PhysRevResearch.5.L022066
Olson, K. A., Chung, C. Y., Aksamit, N. O., Hill, C. E., Brown, C. V. R., & Teixera, P. G. (2023). Rule of four: an anatomic and value-based approach to stent-graft inventory for blunt thoracic aortic injury. European Journal of Trauma and Emergency Surgery, 49, 2173-2176. https://doi.org/10.1007/s00068-023-02267-z
Rypdal, K. (2023). Kausale design – Et gjennombrudd i samfunnsfagene eller keiserens nye klær? Tidsskrift for samfunnsforskning, 64(1), 74-83. https://doi.org/10.18261/tfs.64.1.5

2022

Bianchi, F. M., Grattarola, D., Livi, L., & Alippi, C. (2022). Graph Neural Networks with Convolutional ARMA Filters. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(7), 3496 - 3507. https://doi.org/10.1109/TPAMI.2021.3054830
Bianchi, F. M., Gallicchio, C., & Micheli, A. (2022). Pyramidal Reservoir Graph Neural Network. Neurocomputing, 470, 389 - 404. https://doi.org/10.1016/j.neucom.2021.04.131
Eikeland, O. F., Bianchi, F. M., Holmstrand, I. S., Bakkejord, S., Santos, S., & Chiesa, M. (2022). Uncovering contributing factors to interruptions in the power grid: An Arctic case. Energies, 15, 305. https://doi.org/10.3390/en15010305
Eikeland, O. F., Hovem, F. D., Olsen, T. E., Chiesa, M., & Bianchi, F. M. (2022). Probabilistic forecasts of wind power generation in regions with complex topography using deep learning methods: An Arctic case. Energy Conversion and Management: X, 15, 100239. https://doi.org/10.1016/j.ecmx.2022.100239
Farbu, E. H., Rypdal, M., Skandfer, M., Steingrímsdóttir, Ó. A., Brenn, T., Stubhaug, A.,Nielsen, C. S., & Höper, A. C. (2022). To tolerate weather and to tolerate pain: two sides of the same coin? The Tromsø Study 7. PAIN 163(5), 878-886. https://doi.org/10.1097/j.pain.0000000000002437
Grahn, J., & Bianchi, F. M. (2022). Recognition of polar lows in Sentinel-1 SAR images with deep learning. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-12. https://doi.org/10.1109/tgrs.2022.3204886
Grattarola, D., Zambon, D., Bianchi, F. M., & Alippi, C. (2022). Understanding Pooling in Graph Neural Networks. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2022.3190922
Hansen, J. B., Anfinsen, S. N., & Bianchi, F. M. (2022). Power flow balancing with decentralized graph neural networks. IEEE Transactions on Power Systems, 38(3), 2423-2433. https://doi.org/10.1109/TPWRS.2022.3195301
Jensen, V., Bianchi, F. M., & Anfinsen, S. N. (2022). Ensemble conformalized quantile regression for probabilistic time series forecasting. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2022.3217694
Kleiven, E. F., Nicolau, P. G., Sørbye, S. H., Aars, J., Yoccoz, N. G., & Ims, R. A. (2022). Using camera traps to monitor cyclic vole populations. Remote Sensing in Ecology and Conservation, 1-14. https://doi.org/10.1002/rse2.317
Luppino, L. T., Hansen, M. A., Kampffmeyer, M., Bianchi, F. M., Moser, G., Jenssen, R., & Anfinsen, S. N. (2022). Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2022.3172183
Martinsen, I., Harbitz, A., & Bianchi, F. M. (2022). Age prediction by deep learning applied to Greenland halibut (Reinhardtius hippoglossoides) otolith images. Plos one, 17(11). https://doi.org/10.1371/journal.pone.0277244
Moe, Å. M., Sørbye, S. H., Hopstock, L., Carlsen, M. H., Løvsletten, O., & Ytterstad, E. (2022). Identifying dietary patterns across age, educational level and physical activity level in a cross-sectional study. The Tromsø Study 2015-2016. BMC Nutrition, 8(1), 102. https://doi.org/10.1186/s40795-022-00599-4
Myrvoll-Nilsen, E., Riechers, K., Rypdal, M., & Boers, N. (2022). Comprehensive uncertainty estimation of the timing of Greenland warmings in the Greenland ice core records. Climate of the Past, 18(6), 1275–1294. https://doi.org/10.5194/cp-18-1275-2022
Nicolau, P. G., Ims, R. A., Sørbye, S. H., & Yoccoz, N. G. (2022). Seasonality, density dependence and spatial population synchrony. Proceedings of the National Academy of Sciences, 119(51), e2210144119. https://doi.org/10.1073/pnas.2210144119
Tajsic, N. B., Sørbye, S. H., Nguon, S., Sokh, V., & Lim, A. (2022). Norwegian open fracture management system: Outcomes after 10 years working in low resource settings in Cambodian hospitals. Prehospital and Disaster Medicine, 37(1), 90-100. DOI: 10.1017/S1049023X21001291

2021

Bianchi, F. M., Grahn, J., Eckerstorfer, M., Malnes, E., & Vickers, H. (2021). Snow Avalanche Segmentation in SAR Images With Fully Convolutional Neural Networks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 75-82. https://doi.org/10.1109/JSTARS.2020.3036914
Boers, N., & Rypdal, M. (2021). Critical slowing down suggests that the western Greenland Ice Sheet is close to a tipping point. PNAS, 118(21), e2024192118. https://doi.org/10.1073/pnas.2024192118
Eikeland, O. F., Bianchi, F. M., Apostoleris, H., Hansen, M., Chiou, Y.-C., & Chiesa, M. (2021). Predicting Energy Demand in Semi-Remote Arctic Locations. Energies, 14(4), 798. https://doi.org/10.3390/en14040798
Eikeland, O. F., Holmstrand, I. S., Bakkejord, S., Chiesa, M., & Bianchi, F. M. (2021). Detecting and interpreting faults in vulnerable power grids with machine learning. IEEE Access, 9, 150686 - 150699. https://doi.org/10.1109/ACCESS.2021.3127042
Juhász, D., & Jakobsen, P. K. (2021). Modelling pulse propagation in complex index materials using the method of multiple scales. Physica Scripta, 96, 115503. https://doi.org/10.1088/1402-4896/ac1547
Lewkowski, K., Ytterstad, E., Pugliese, M. J., McCausland, K., Heyworth, J., Li, I. W., ... Fritschi, L. (2021). Exposure to hand-arm vibration in the Australian workforce. Annals of Work Exposures and Health, 65(6), 659-667. https://doi.org/10.1093/annweh/wxaa121
Lewkowski, K., Heyworth, J., Ytterstad, E., Williams, W., Goulios, H., & Fritschi, L. (2021). The prevalence of tinnitus in the Australian working population. Medical Journal of Australia, 216(4), 189-193. https://doi.org/10.5694/mja2.51354
Luppino, L. T., Kampffmeyer, M., Bianchi, F. M., Moser, G., Serpico, S. B., Jenssen, R., & Anfinsen, S. N. (2021). Deep image translation with an affinity-based change prior for unsupervised multimodal change detection. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-22. https://doi.org/10.1109/TGRS.2021.3056196
Mansuripur, M., & Jakobsen, P. K. (2021). Theoretical analysis of Fresnel reflection and transmission in the presence of gain media. Optical Review, 28(6), 626-649. https://doi.org/10.1007/s10043-021-00690-4
Mansuripur, M., & Jakobsen, P. K. (2021). Fresnel reflection and transmission in the presence of gain media. In Proc. SPIE 11797, Plasmonics: Design, Materials, Fabrication, Characterization, and Applications XIX, 117971G. https://doi.org/10.1117/12.2595188
Mikalsen, K. Ø., Soguero-Ruiz, C., Bianchi, F. M., Revhaug, A., & Jenssen, R. (2021). Time series cluster kernels to exploit informative missingness and incomplete label information. Pattern Recognition, 115, 107896. https://doi.org/10.1016/j.patcog.2021.107896
Ren, H., Bianchi, H. M., Li, J., Olsen, R. L., Jenssen, R. & Anfinsen, S. N. (2021). Towards applicability: A comparative study on non-intrusive load monitoring algorithms. Proceedings of the 2021 IEEE International Conference on Consumer Electronics. https://doi.org/10.1109/ICCE50685.2021.9427652
Rypdal, K. (2021). The tipping effect of delayed interventions on the evolution of COVID-19 incidence. International Journal of Environmental Research and Public Health, 18(9), 4484. https://doi.org/10.3390/ijerph18094484
Rypdal, M., Boers, N., Fredriksen, H.-B., Eiselt, K.-U., Johansen, A., Martinsen, A., Mentzoni, E. F., Graversen, R. G. & Rypdal, K. (2021). Estimating remaining carbon budgets using temperature responses informed by CMIP6. Frontiers in Climate, 3. https://doi.org/10.3389/fclim.2021.686058
Rypdal, M., Rypdal, K., Løvsletten, O., Sørbye, S. H., Ytterstad, E., & Bianchi, F. M. (2021). Estimation of excess mortality and years of life lost to COVID-19 in Norway and Sweden between March and November 2020. Int. J. Environ. Res. Public Health, 18(8), 3913. https://doi.org/10.3390/ijerph18083913
Rypdal, M., Rypdal, V., Jakobsen, P., Ytterstad, E., Løvsletten, O., Klingenberg, C., & Rypdal, K. (2021). Modelling suggests limited change in the reproduction number from reopening Norwegian kindergartens and schools during the COVID-19 pandemic. Plos One, 16(2): e0238268. https://doi.org/10.1371/journal.pone.0238268
Sørbye, S. H., Nicolau, P. G., & Rue, H. (2021). Finite sample properties of estimators for first and second order autoregressive processes. Statistical Inference for Stochastic Processes, 25, 577-598. https://doi.org/10.1007/s11203-021-09262-4

2020

Bianchi, F. M., Grattarola, D., Livi, L., & Alippi, C. (2020). Hierarchical representation learning in graph neural networks with node decimation pooling. IEEE Transactions on Neural Networks and Learning Systems, 33(5), 2195 – 2207. https://doi.org/10.1109/TNNLS.2020.3044146
Franzke, C. L. E., Barbosa, S., Blender, R., Fredriksen, H.-B., Laepple, T., Lambert, F., Nilsen, T., Rypdal, K., Rypdal, M., et al. (2020). The structure of climate variability across scales. Reviews of Geophysics, 58(2), e2019RG000657. https://doi.org/10.1029/2019RG000657
Haug, O., Thorarinsdottir, T. L., Sørbye, S. H., & Franzke, C. (2020). Spatial trend analysis of gridded temperature data sets at varying spatial scales. Advances in Statistical Climatology, Meteorology and Oceanography, 6, 1-12. https://doi.org/10.5194/ascmo-6-1-2020
Henrey A., V. Rypdal, M. Rypdal, T. Loughin, E. Nordal, and J. Guzman, for the ReACCh-Out and NoSPeR Investigators (2019). Validation of prediction models of severe disease course and non-achievement of remission in juvenile idiopathic arthritis part 2: results of the Nordic model in the Canadian cohort, Arthritis Research & Therapy, 22, 10. https://doi.org/10.1186/s13075-019-2091-8
Jakobsen, P. K., & Mansuripur, M. (2020). On the nature of the Sommerfeld-Brillouin Forerunners (or Precursors). Quantum Studies: Mathematics and Foundations, 7, 315-339. https://doi.org/10.1007/s40509-019-00210-9
Lin, A., Kuzmina, A., & Jakobsen, P. K. (2020). A boundary integral approach to linear and nonlinear transient scattering. Applied Numerical Mathematics, 147, 277-300. https://doi.org/10.1016/j.apnum.2019.08.026
Mansuripur, M., & Jakobsen, P. K. (2020). Electromagnetic radiation and the self torque of an oscillating magnetic dipole. In Proc. SPIE 11462, Plasmonics: Design, Materials, Fabrication, Characterization, and Applications XVIII, 114620W. https://doi.org/10.1117/12.2569137
Mansuripur, M., & Jakobsen, P. K. (2020). Electromagnetic radiation and the self-field of a spherical dipole oscillator. American Journal of Physics, 88, 693–703. https://doi.org/10.1119/10.0001348
Myrvoll-Nilsen, E., Sørbye, S. H., Fredriksen, H.-B., Rue, H., & Rypdal, M. (2020). Statistical estimation of global surface temperature response to forcing under the assumption of temporal scaling. Earth System Dynamics, 11, 329-345. https://doi.org/10.5194/esd-11-329-2020
Nicolau, P. G., Sørbye, S. H., & Yoccoz, N. G. (2020). Incorporating capture heterogeneity in the estimation of autoregressive coefficients of animal population dynamics using capture-recapture data. Ecology and Evolution, 10(23), 12710--12726. https://doi.org/10.1002/ece3.6642
Nova, N., Deyle, E. R., Shocket, M. S., MacDonald, A. J., Childs, M. L., Rypdal, M., Sugihara, G., & Mordecai, E. A. (2020). Susceptible host availability modulates climate effects on dengue dynamics. Ecology Letters, 24(3), 415-425, https://doi.org/10.1111/ele.13652
Rypdal, K., Bianchi, F. M., & Rypdal, M. (2020). Intervention fatigue is the primary cause of strong secondary waves in the COVID-19 pandemic. International Journal of Environmental Research and Public Health, 17(24), 9592. https://doi.org/10.3390/ijerph17249592
Rypdal, K., & Rypdal, M. (2020). A parsimonious description and cross-country analysis of COVID-19 epidemic curves. International Journal of Environmental Research and Public Health, 17(18), 6487. https://doi.org/10.3390/ijerph17186487

2019

Flores, L., Lensing, M. B., Ytterstad, E., & Eisemann, M. (2019). Quality of life in substance use disorder patients with and without attention deficit hyperactivity disorder 12 months after treatment: a naturalistic follow-up study. ADHD Attention Deficit and Hyperactivity Disorders, 11, 299-310. https://doi.org/10.1007/s12402-019-00297-5
Hofstrand, A., Jakobsen, P. K., & Molone, J. V. (2019). Bidirectional shooting method for extreme nonlinear optics. Physical Review A, 100, 053818. https://doi.org/10.1103/PhysRevA.100.053818
Juhász, D., & Jakobsen, P. K. (2019). Constructing a partially transparent computational boundary for UPPE using leaky modes. Journal of Mathematical Physics, 60, 083505. https://doi.org/10.1063/1.5099193
Lewkowski, K., Heyworth, J. S., Li, I. W., Williams, W., McCausland, K., Gray, C., ... Fritschi, L. (2019). Exposure to noise and ototoxic chemicals in the Australian workforce. Occupational and Environmental Medicine, 76(5), 341-348. https://doi.org/10.1136/oemed-2018-105471
Lin, A., & Jakobsen, P. K. (2019). A 3D nonlinear Maxwell's equations solver based on a hybrid numerical method. Physica Scripta, 94, 085211. https://doi.org/10.1088/1402-4896/ab166d
Lin, A., & Jakobsen, P. K. (2019). On the Ewald Oseen scattering formulation for light scattering: Stability, singularity and parallelization. Physica Scripta, 95, 015201. https://doi.org/10.1088/1402-4896/ab3d0d
Mansuripur, M., & Jakobsen, P. K. (2019). An approach to constructing super oscillatory functions. Journal of Physics A: Mathematical and Theoretical, 52, 305202. https://doi.org/10.1088/1751-8121/ab27de
Myrvoll-Nilsen, E., Fredriksen, H.-B., Sørbye, S. H., & Rypdal, M. (2019). Warming trends and long-range dependent climate variability since the year 1900: a Bayesian approach. Frontiers in Environmental Science, 7. https://doi.org/10.3389/feart.2019.00214
Rypdal, M., & Sugihara, G. (2019). Inter-outbreak stability reflects the size of the susceptible pool and forecasts magnitudes of seasonal epidemics. Nature Communications, 10, 2374. https://doi.org/10.1038/s41467-019-10099-y
Rypdal, V., Guzman, J., Henrey, A., Loughin, T., Glerup, M., Arnstad, E. D., ... & Nordal, E. (2019). Validation of prediction models of severe disease course and non-achievement of remission in juvenile idiopathic arthritis: Part 1—results of the Canadian model in the Nordic cohort. Arthritis Research & Therapy, 21, 270. https://doi.org/10.1186/s13075-019-2060-2
Sørbye, S. H., Myrvoll-Nilsen, E., & Rue, H. (2019). An approximate fractional Gaussian noise model with O(n) computational cost. Statistics and Computing, 29, 821-833. https://doi.org/10.1007/s11222-018-9843-1
Sørbye, S. H., Illian, J. B., Simpson, D., Burslem, D. F. R. P., & Rue, H. (2019). Careful prior specification avoids incautious inference for log-Gaussian Cox point processes. Journal of the Royal Statistical Society Series C: Applied Statistics, 68(3), 543-564. https://doi.org/10.1111/rssc.12321

2018

Devenish, G., Ytterstad, E., Begley, A., Do, L., & Scott, J. (2018). Intake, sources and determinants of free sugars intake in Australian children aged 12-14 months. Maternal & Child Nutrition, 15(2). https://doi.org/10.1111/mcn.12692
Jakobsen, P. K., Mansuripur, M., & Kolesik, M. (2018). Leaky-mode expansion of the electromagnetic field inside a dispersive spherical cavity. Journal of Mathematical Physics, 59, 033501. https://doi.org/10.1063/1.5006956
Juhász, D., Kolesik, M., & Jakobsen, P. K. (2018). Convergence and completeness for square-well Stark resonant state expansions. Journal of Mathematical Physics, 59, 113501. https://doi.org/10.1063/1.5042523
Nilsen, T., Werner, J. P., Divine, D. V., & Rypdal, M. (2018). Assessing the performance of the BARCAST climate field reconstruction technique for a climate with long-range memory. Climate of the Past, 14, 947–967. https://doi.org/10.5194/cp-14-947-2018
Rypdal, K. (2018). The life and death of the recent global surface warming hiatus parsimoniously explained. Climate, 6(3), 64. https://doi.org/10.3390/cli6030064
Rypdal, K. (2018). Empirical growth models for the renewable energy sector. Advances in Geosciences, 45, 35-44. https://doi.org/10.5194/adgeo-45-35-2018
Rypdal, M., Fredriksen, H.-B., Rypdal, K., & Steene, R. (2018). Emergent constraints on climate sensitivity. Nature, 563, E4–E5. https://doi.org/10.1038/s41586-018-0639-4
Rypdal, M., Fredriksen, H.-B., Myrvoll-Nilsen, E., Rypdal, K., & Sørbye, S. H. (2018). Emergent scale invariance and climate sensitivity. Climate, 6(4), 93. https://doi.org/10.3390/cli6040093
Rypdal, M., Rypdal, V., Burney, J. A., Cayan, D., Bainto, E., Skochko, S., ... & Burns, J. C. (2018). Clustering and climate associations of Kawasaki Disease in San Diego County suggest environmental triggers. Scientific Reports, 8, 16140. https://doi.org/10.1038/s41598-018-33124-4
Rypdal, V., Arnstad, E. D., Aalto, K., Berntson, L., Ekelund, M., Fasth, A., ... & Nordal, E. (2018). Predicting unfavorable long-term outcome in juvenile idiopathic arthritis: Results from the Nordic cohort study. Arthritis Research & Therapy, 20, 91. https://doi.org/10.1186/s13075-018-1571-6
Sørbye, S. H., & Rue, H. (2018). Fractional Gaussian noise: Prior specification and model comparison. Environmetrics, 29, e2457. https://doi.org/10.1002/env.2457
Ytterstad, E. (2018). Frailty in survival analysis of widowhood mortality. Journal of Probability and Statistics, 2018, 2378798. https://doi.org/10.1155/2018/2378798

2017

Fredriksen, H.-B., & Rypdal, M. (2017). Long-range persistence in global surface temperatures explained by linear multi-box energy balance models. Journal of Climate, 30, 7157–7168. https://doi.org/10.1175/JCLI-D-16-0877.1
Karlsen, G. R., & Ytterstad, E. (2017). Leakage from medically-certified to self-certified workplace absence among Norwegian employees. Society, Health & Vulnerability, 8, 1411119. https://doi.org/10.1080/20021518.2017.1411119
Mansuripur, M., Kolesik, M., & Jakobsen, P. K. (2017). Leaky modes of solid dielectric spheres. Physical Review A, 96, 013846. https://doi.org/10.1103/PhysRevA.96.013846
Måløy, M., Måløy, F., Jakobsen, P. K., & Brandsdal, B. O. (2017). Dynamic self-organisation of haematopoiesis and (a)symmetric cell division. Journal of Theoretical Biology, 414, 147-164. https://doi.org/10.1016/j.jtbi.2016.11.030
Rue, H., Riebler, A. I., Sørbye, S. H., Illian, J. B., Simpson, D., & Lindgren, F. K. (2017). Bayesian Computing with INLA: A Review. Annual Review of Statistics and Its Application, 4, 395-421. https://doi.org/10.1146/annurev-statistics-060116-054045
Simpson, D., Rue, H., Riebler, A. I., Martins, T. G., & Sørbye, S. H. (2017). You just keep on pushing my love over the borderline: A rejoinder. Statistical Science, 32(1), 44-46. https://doi.org/10.1214/17-STS576REJ
Simpson, D., Rue, H., Riebler, A. I., Martins, T. G., & Sørbye, S. H. (2017). Penalising model component complexity: A principled, practical approach to constructing priors. Statistical Science, 32(1), 1-28. https://doi.org/10.1214/16-STS576
Strøm, J. F., Thorstad, E. B., Chafe, G., Sørbye, S. H., Righton, D., Rikardsen, A. H., & Carr, J. (2017). Ocean migration of pop-up satellite archival tagged Atlantic salmon from the Miramichi River in Canada. ICES Journal of Marine Science, 74(5), 1356–1370. https://doi.org/10.1093/icesjms/fsw220
Sørbye, S. H., & Rue, H. (2017). Penalised Complexity Priors for Stationary Autoregressive Processes. Journal of Time Series Analysis, 38(6), 923-935. https://doi.org/10.1111/jtsa.12242
Theodorsen, A., Garcia, O. E., & Rypdal, M. (2017). Statistical properties of a filtered Poisson process with additive random noise: Distributions, correlations, and moment estimation. Physica Scripta, 92(5), 054002. https://doi.org/10.1088/1402-4896/aa694c

2016

Brenn, T., & Ytterstad, E. (2016). Increased risk of death immediately after losing a spouse: Cause-specific mortality following widowhood in Norway. Preventive Medicine, 89, 251-256. https://doi.org/10.1016/j.ypmed.2016.06.019
Brown, J., Jakobsen, P., Bahl, A., Moloney, J. V., & Kolesik, M. (2016). On the convergence of quantum resonant-state expansion. Journal of Mathematical Physics, 57, 032105. https://doi.org/10.1063/1.4944625
Flores, L., Ytterstad, E., Lensing, M. B., & Eisemann, M. (2016). Exploring Personality and Readiness to Change in Patients With Substance Use Disorders With and Without ADHD. Journal of Attention Disorders, 24(9), 1255-1265. https://doi.org/10.1177/1087054716677819
Fredriksen, H. - B. & Rypdal, K. (2016). Spectral characteristics of instrumental and climate model surface temperatures. Journal of Climate, 29(4), 1253 - 1268. https://doi.org/10.1175/JCLI-D-15-0457.1
Lorentzen, G. E., Egeness, F.-A., Pleym, I. E., & Ytterstad, E. (2016). Shelf life of packaged loins of dried salt-cured cod (Gadus morhua L.) stored at elevated temperatures. Food Control, 64, 65-69. https://doi.org/10.1016/j.foodcont.2015.12.027
Løvsletten, O., & Rypdal, M. (2016). Statistics of Regional Surface Temperatures after 1900: Long-Range versus Short-Range Dependence and Significance of Warming Trends. Journal of Climate, 29(11), 4057-4068. https://doi.org/10.1175/JCLI-D-15-0437.1
Mansuripur, M., Kolesik, M., & Jakobsen, P. (2016). Leaky modes of dielectric cavities. Proceedings of SPIE 9931, Spintronics IX, 99310B. https://doi.org/10.1117/12.2237904
Nilsen, T., Rypdal, K. & Fredriksen, H.-B. (2016). Are there multiple scaling regimes in Holocene temperature records? Earth System Dynamics 7, 419–439, https://doi.org/10.5194/esd-7-419-2016
Riebler, A., Sørbye, S. H., Simpson, D. P., & Rue, H. (2016). An intuitive Bayesian spatial model for disease mapping that accounts for scaling. Statistical Methods in Medical Research, 25(4), 1145–1165. https://doi.org/10.1177/0962280216660421
Rypdal, K. (2016). Global warming projections derived from an observation-based minimal model. Earth System Dynamics, 7, 51-70. https://doi.org/10.5194/esd-7-51-2016
Rypdal, K., & Rypdal, M. (2016). Comment on "Scaling regimes and linear/nonlinear responses of last millennium climate to volcanic and solar forcing" by S. Lovejoy and C. Varotsos. Earth System Dynamics, 7, 597-609. https://doi.org/10.5194/esd-7-597-2016
Rypdal, M. (2016). Early-warning signals for the onsets of Greenland Interstadials and the Younger Dryas-Preboreal transition. Journal of Climate, 29(11), 4047-4056. https://doi.org/10.1175/JCLI-D-15-0828.1
Rypdal, M., & Rypdal, K. (2016). Late Quaternary temperature variability described as abrupt transitions on a 1/f noise background. Earth System Dynamics, 7, 281-293. https://doi.org/10.5194/esd-7-281-2016
Simpson, D., Illian, J., Lindgren, F., Sørbye, S. H., & Rue, H. (2016). Going off grid: computationally efficient inference for log-Gaussian Cox processes. Biometrika, 103(1), 49–70. https://doi.org/10.1093/biomet/asv064
Ytterstad, E., Moe, P. C., & Hjalmarsen, A. (2016). COPD in primary lung cancer patients: Prevalence and mortality. The International Journal of Chronic Obstructive Pulmonary Disease, 23(11), 625-636. https://doi.org/10.2147/COPD.S101183

2015:

Høyem, M. R., Måløy, F., Jakobsen, P., & Brandsdal, B. O. (2015). Stem cell regulation: Implications when differentiated cells regulate symmetric stem cell division. Journal of Theoretical Biology, 378, 1-9. https://doi.org/10.1016/j.jtbi.2015.05.009
Jakobsen, P. K. (2015). Exact formula for the high harmonic response of a strongly driven two-level system. Physica Scripta, 90, 025501. https://doi.org/10.1088/0031-8949/90/2/025501
Mykhaylyk, R., & Ytterstad, E. (2015). Directionality of cross-linguistic influence: Which referring choices do bilingual Ukrainian–English children make? International Journal of Bilingualism, 21(1), 99-121. https://doi.org/10.1177/1367006915603824
Rypdal, K. (2015). Attribution in the presence of a long-memory climate response. Earth System Dynamics, 6, 719-730. https://doi.org/10.5194/esd-6-719-2015
Rypdal, K., Rypdal, M., & Fredriksen, H.-B. (2015). Spatiotemporal long-range persistence in earth's temperature field: Analysis of stochastic-diffusive energy balance models. Journal of Climate, 28(21), 8379-8395. https://doi.org/10.1175/jcli-d-15-0183.1
Ytterstad, E., & Brenn, T. (2015). Mortality After the Death of a Spouse in Norway. Epidemiology, 26(3), 289-294. https://doi.org/10.1097/EDE.0000000000000266

2014:

Aune, T. F., Olsen, R. L., Akse, L., Ytterstad, E., & Esaiassen, M. (2014). Influence of different cold storage temperatures during the Rigor mortis phase on fillet contraction and longer-term quality changes of Atlantic cod fillets. LWT - Food Science and Technology, 59(1), 583-586. https://doi.org/10.1016/j.lwt.2014.04.018
Bahl, A., Teleki, A., Jakobsen, P. K., Wright, E., & Kolesik, M. (2014). Reflectionless Beam Propagation on a Piecewise Linear Complex Domain. Journal of Lightwave Technology, 32(22), 3670-3676 https://doi.org/10.1109/JLT.2014.2354631
Jakobsen, P. K. (2014). Bidirectional pulse propagation equation for extreme nonlinear optics. Physica Scripta, 89, 015301. https://doi.org/10.1088/0031-8949/89/9/095502
Kilen, I. R., & Jakobsen, P. K. (2014). Computing the Casimir force using regularized boundary integral equations. Physica Scripta, 89, 115205. https://doi.org/10.1088/0031-8949/89/11/115205
Kolesik, M., Brown, J. M., Teleki, A., Jakobsen, P. K., Moloney, J. V., & Wright, E. M. (2014). Metastable electronic states and nonlinear response for high-intensity optical pulses. Optica, 1(5), 323-331. https://doi.org/10.1364/OPTICA.1.000323
Rypdal, M., & Rypdal, K. (2014). Long-memory effects in linear response models of Earth's temperature and implications for future global warming. Journal of Climate, 27(14), 5240-5258. https://doi.org/10.1175/JCLI-D-13-00296.1
Sørbye, S. H., & Rue, H. (2014). Scaling intrinsic Gaussian Markov random field priors in spatial modeling. Spatial Statistics, 8, 39-51. https://doi.org/10.1016/j.spasta.2013.06.004
Østvand, L., Nilsen, T., Rypdal, K., Divine, D., & Rypdal, M. (2014). Long-range memory in internal and forced dynamics of millennium-long climate model simulations. Earth System Dynamics, 5(2), 295-308. https://doi.org/10.5194/esd-5-295-2014

2013:

Illian, J. B., Martino, S., Sørbye, S. H., Gallego-Fernandez, J. B., Zunzunegui, M., Paz Esquivias, M., & Travis, J. (2013). Fitting complex ecological point process models with integrated nested Laplace approximation (INLA). Methods in Ecology and Evolution, 4, 305–315. https://doi.org/10.1111/2041-210x.12017
Rypdal, K., Østvand, L., & Rypdal, M. (2013). Long-range memory in Earth's surface temperature on time scales from months to centuries. Journal of Geophysical Research: Atmospheres, 118(13), 7046-7062. https://doi.org/10.1002/jgrd.50399
Rypdal, M., & Løvsletten, O. (2013). Modeling electricity spot prices using mean-reverting multifractal processes. Physica A: Statistical Mechanics and its Applications, 392(1), 194-207. https://doi.org/10.1016/j.physa.2012.08.004
Rypdal, M., Sirnes, E., Løvsletten, O., & Rypdal, K. (2013). Assessing market uncertainty by means of a time-varying intermittency parameter for asset price fluctuations. Physica A: Statistical Mechanics and its Applications, 392(16), 3335-3343. https://doi.org/10.1016/j.physa.2013.02.010
Zivkovic, T. & Rypdal, K. (2013). ENSO dynamics: Low-dimensional-chaotic or stochastic? Journal of Geophysical Research, 118, 2161-2168. https://doi.org/10.1002/jgrd.50190

2012:

Illian, J. B., Sørbye, S. H., & Rue, H. (2012). A toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA). Annals of Applied Statistics, 6, 1499–1530. https://doi.org/10.1214/11-AOAS530
Jakobsen, P. K., & Moloney, J. V. (2012). The effect of longitudinal electric field components on the propagation of intense ultrashort optical pulses. Physica D: Non-linear Phenomena, 241(19), 1603-1611. https://doi.org/10.1016/j.physd.2012.06.004
Kolesik, M., Jakobsen, P. K., & Moloney, J. V. (2012). Quantifying the limits of unidirectional ultrashort optical pulse propagation. Physical Review A, 86, 035801. https://doi.org/10.1103/PHYSREVA.86.035801
Rypdal, K. (2012). Global temperature response to radiative forcing: Solar cycle versus volcanic eruptions. Journal of Geophysical Research, 117, D6. https://doi.org/10.1029/2011JD017283
Rypdal, K., & Rypdal, M. (2012). Stochastic properties of solar activity proxies. Astrophysics and Space Science Proceedings, 33, 227-232. https://doi.org/10.1007/978-3-642-30442-2_25
Rypdal, M., & Rypdal, K. (2012). Is there long-range memory in solar activity on timescales shorter than the sunspot period? Journal of Geophysical Research - Space Physics, 117, A04103. https://doi.org/10.1029/2011JA017283

Members

Funded projects

News

Complex Systems Modeling

Members

Jonas Berg Hansen – Doctoral Research Fellow

Sigrunn Holbek Sørbye – Professor

Clara Hummel – Doctoral Research Fellow

Filippo Maria Bianchi – Associate Professor

Markus Held – Associate Professor

Nikolas Olson Aksamit – Associate Professor

Michele Guerra – Doctoral Research Fellow

Martin Rypdal – Professor/Instituttleder

Eirik Myrvoll-Nilsen – Postdoctoral Fellow

Alessandro Cotronei – Doctoral Research Fellow

Kristoffer Rypdal – Professor

Per Kristen Jakobsen – Professor

Åse Mari Moe – Doctoral Research Fellow

Nils Bochow – Postdoc

Anna Poltronieri – Doctoral Research Fellow

Luc Ludovic Nicolas Hallali – Doctoral Research Fellow

Rebekka Jastamin Steene – Doctoral Research Fellow

Elinor Ytterstad – Associate Professor

Funded projects

RELAY: Relational Deep Learning for Energy Analytics

Stability of the Arctic Climate

DYNAMO - UiT Aurora Centre for Nonlinear Dynamics and Complex Systems Modeling

News

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Complex Systems Modeling

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