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Results: 218,660
Number of items: 218,660
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Lippert, F., Kranstauber, B., Forré, P. D., & van Loon, E. E. (2022). Learning to predict spatiotemporal movement dynamics from weather radar networks. Methods in Ecology and Evolution, 13(12), 2811-2826. https://doi.org/10.1111/2041-210X.14007 -
Deserno, M. K., Isvoranu, A.-M., Epskamp, S., & Blanken, T. F. (2022). Descriptive Analysis of Network Structures. In A.-M. Isvoranu, S. Epskamp, L. Waldorp, & D. Borsboom (Eds.), Network Psychometrics with R: A Guide for Behavioral and Social Scientists (pp. 45-65). (Research methods and statistics). Routledge. https://doi.org/10.4324/9781003111238-4
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Weinland, D. H., van der Maas, K., Wang, Y., Bottega Pergher, B., van Putten, R. J., Wang, B., & Gruter, G. J. M. (2022). Overcoming the low reactivity of biobased, secondary diols in polyester synthesis. Nature Communications, 13, Article 7370. https://doi.org/10.1038/s41467-022-34840-2
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Ventouri, I. K., Loeber, S., Somsen, G. W., Schoenmakers, P. J., & Astefanei, A. (2022). Field-flow fractionation for molecular-interaction studies of labile and complex systems: A critical review. Analytica Chimica Acta, 1193, Article 339396. https://doi.org/10.1016/j.aca.2021.339396
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Antorán, J., Janz, D., Allingham, J. U., Daxberger, E., Barbano, R., Nalisnick, E., & Hernández-Lobato, J. M. (2022). Adapting the Linearised Laplace Model Evidence for Modern Deep Learning. Proceedings of Machine Learning Research, 162, 796-821. https://doi.org/10.48550/arXiv.2206.08900
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Martins, A. F. T., Treviso, M., Farinhas, A., Aguiar, P. M. Q., Figueiredo, M. A. T., Blondel, M., & Niculae, V. (2022). Sparse continuous distributions and Fenchel-Young losses. Journal of Machine Learning Research, 23, Article 257. https://www.jmlr.org/papers/v23/21-0879.html
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Bergstra, J. A., & Tucker, J. V. (2022). Partial arithmetical data types of rational numbers and their equational specification. Journal of Logical and Algebraic Methods in Programming, 128, Article 100797. https://doi.org/10.1016/j.jlamp.2022.100797
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Dalege, J., Haslbeck, J. M. B., & Marsman, M. (2022). Idealized Modeling of Psychological Dynamics. In A.-M. Isvoranu, S. Epskamp, L. Waldrop, & D. Borsboom (Eds.), Network Psychometrics with R: A Guide for Behavioral and Social Scientists (pp. 233-245). (Research methods and statistics). Routledge. https://doi.org/10.4324/9781003111238-17
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Ikefuji, M., Laeven, R. J. A., Magnus, J. R., & Yue, Y. (2022). Earthquake risk embedded in property prices: Evidence from five Japanese cities. Journal of the American Statistical Association, 117(537), 82-93. https://doi.org/10.1080/01621459.2021.1928512
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