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Feliu, E., Knudsen, M., Wiuf, C. H. & Andersen, L. N. (2010). An Algebraic Approach to Signaling Cascades with n Layers. Poster-session præsenteret på The 11th International Conference on Systems Biology, Edinburgh, Storbritannien.
Exarchakos, G., van der Hofstad, R., Nagy, O. & Pandey, M. (2026). Bringing order to network centrality measures. (s. 1-24). ArXiv. https://arxiv.org/abs/2601.16236
Engholm, R., Karstoft, H. & Jensen, E. B. V. (2009). Adaptive kernel filtering used in video processing. I Visual Communications and Image Processing 2009 (s. 72571E). SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.808155
Embrechts, P., Jensen, J. L., Maejima, M. & Teugels, J. L. (1985). Approximations for compound Poisson and Pólya processes. Advances in Applied Probability, 17(3), 623-637. https://doi.org/10.2307/1427123
Elmholt, S. & Labouriau, R. (2005). Fungi in Danish soils under organic and conventional farming. Agriculture, Ecosystems and Environment, 107, 65-73.
Egendal, I., Brøndum, R. F., Pelizzola, M., Hobolth, A. & Bøgsted, M. (2025). On the Relation Between Linear Autoencoders and Non-Negative Matrix Factorization for Mutational Signature Extraction. Journal of computational biology : a journal of computational molecular cell biology, 32(5), 461-472. https://doi.org/10.1089/cmb.2024.0784
Dorph-Petersen, K.-A., Gundersen, H. J. G., Jensen, E. B. V. & Kiêu, K. (2001). Non-uniform systematic sampling for area estimation of planar objects. I C. Babu Rao, P. Kalyanasundaram, KK. Ray & B. Raj (red.), Image Analysis in Materials and Life Sciences (s. 4-8)
Dorph-Petersen, K.-A., Ziegel, J., Baddeley, A. & Jensen, E. B. V. (2016). Prediction of the variance of stereological volume estimates in systematic sampling with errors in sampling locations. Abstract fra AU Workshop on Stochastic Geometry, Stereology and their Applications, Sønderborg, Danmark.
Dörnemann, N. & Dette, H. (2024). Linear spectral statistics of sequential sample covariance matrices. Annales de l'institut Henri Poincare (B) Probability and Statistics, 60(2), 946-970. https://doi.org/10.1214/22-AIHP1339
Dormann, F., Frisk, O., Andersen, L. N. & Pedersen, C. F. (2021). Not All Noise Is Accounted Equally: How Differentially Private Learning Benefits From Large Sampling Rates. I 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing, MLSP 2021 IEEE. https://doi.org/10.1109/MLSP52302.2021.9596307
Deutch, S., Labouriau, R., Schønheyeder, H. C., Østergaard, L. & Sørensen, H. T. (2004). Crowding as a Risk Factor of Meningococcal Disease in Danish Prescholl Children: A Nationwide Population-based Case-control Study. Scandinavian Journal of Infectious Diseases, 36(1), 20-23. https://doi.org/10.1080/00365540310017500
Demétrio, C. G. B., Maia, R. P. & Labouriau, R. (2015). A competing risk model for discrete time with masked causes and gaussian random component.. Abstract fra The 8th Conference of the Eastern Mediterranean Region International Biometric Society, Tyrkiet.