Publications of the IDA Lab since project start (March 2020)

[36] J. Pilz, L. Hehenwarter, G. Zimmermann, G. Rendl, G. Schweighofer-Zwink, M. Beheshti, C. Pirich: Feasibility of equivalent performance of 3D TOF [18F]-FDG PET/CT with reduced acquisition time using clinical and semiquantitative parameters. EJNMMI Res. 11(1):44 (2021),

[35] J. Fernández Sánchez, W. Trutschnig, M. Tschimpke: Markov product invariance in classes of bivariate copulas characterized by univariate functions. Journal of Mathematical Analysis and Applications 501(2), 125184 (2021),

[34] T. Mroz, S. Fuchs, W. Trutschnig: How simplifying and flexible is the simplifying assumption in pair-copula constructions – analytic answers in dimension three and a glimpse beyond. Electronic Journal of Statistics 15, 1951-1992 (2021),

[33] A. Schenk, M. Neuhäuser, G.D. Ruxton, A.C. Bathke: Predictors of pre-European deforestation on Pacific islands: A re-analysis using modern multivariate non-parametric statistical methods. Forest Ecology and Management (2021)

[32] F. Graf, C.D. Hofer, M. Niethammer and R. Kwitt: Dissecting Supervised Constrastive Learning (2021)

[31] V. Racher and C. Borgelt: Gradient Ascent for Best Response Regression. 19th Symposium on Intelligent Data Analysis 2021

[30] T. Kiesslich, M. Beyreis, G. Zimmermann and A. Traweger: Citation inequality and the Journal Impact Factor: median, mean, (does it) matter? Scientometrics (2021)

[29] S. Fuchs, F.M.L. Di Lascio and F. Durante: Dissimilarity functions for rank-based hierarchical clustering of continuous variables. to appear in Computational Statistics and Data Analysis (2021)

[28] E. Brunner, F. Konietschke, A.C. Bathke and M. Pauly: Ranks and Pseudo-ranks—Surprising Results of Certain Rank Tests in Unbalanced Designs. International Statistical Review (2020)

[27] F. Durante, J. Fernández Sánchez, W. Trutschnig, M. Úbeda-Flores: On the size of subclasses of quasi-copulas and their Dedekind-MacNeille completion. Mathematics (2020)

[26]  S. Hirländer, N. Bruchon: Model-free and Bayesian Ensembling Model-based Deep Reinforcement Learning for Particle Accelerator Control Demonstrated on the FERMI FEL (2020)

[25] A. Kovacs-Györi, A. Ristea, C. Havas, M. Mehaffy, H.H. Hochmair, B. Resch, L. Juhasz, A. Lehner, L. Ramasubramanian, T. Blaschke: Opportunities and Challenges of Geospatial Analysis for Promoting Urban Livability in the Era of Big Data and Machine Learning. ISPRS Int. J. Geo-Inf. (2020)

[24] V. Kain, S. Hirländer, B. Goddard, F.M.Velotti, G. Zevi Della Porta, N. Bruchon, G.  Valentino: Sample-efficient reinforcement learning for CERN accelerator control. Physical Review Accelerators and Beams (2020)

[23] T. Kasper, S. Fuchs, W. Trutschnig: On weak conditional convergence of bivariate Archimedean and Extreme Value copulas, and consequences to nonparametric estimation. to appear in Bernoulli (2020),, preprint.pdf

[22] S. Fuchs, W. Trutschnig: On quantile-based co-risk measures and their estimation. Dependence Modeling (2020)

[21] F. Durante, J. Fernández Sánchez, C. Ignazzi, W. Trutschnig: On extremal problems for pairs of uniformly distributed sequences and integrals with respect to copula measures. to appear in Uniform Distribution Theory  (2020)

[20] G. Zimmermann: To rank or to permute when comparing an ordinal outcome between two groups while adjusting for a covariate? In: La Rocca et al. (eds.), Nonparametric Statistics. 4th ISNPS, Salerno, Italy, Springer Proceedings in Mathematics and Statistics (2018)

[19] A. Egger-Rainer, E. Trinka, G. Zimmermann, S. Arnold, C. Boßelmann, H. Hamer, A. Hengsberger, J. Lang, H. Lerche, S. Noachtar, E. Pataraia, A. Schulze-Bonhage, A.M. Staack, I. Unterberger, S. Lorenzl: Assessing comfort in the epilepsy monitoring unit: Psychometric testing of an instrument. Epilepsy Behav (2020)

[18] M. Leitinger, K.N. Poppert, M. Mauritz, F. Rossini, G. Zimmermann, A. Rohracher, G. Kalss, G. Kuchukhidze, J. Höfler, P. Bosque Varela, R. Kreidenhuber, K. Volna, C. Neuray, T. Kobulashvili, C.A. Granbichler, U. Siebert, E. Trinka: Status epilepticus admissions during the COVID-19 pandemic in Salzburg. A population-based study. Epilepsia (2020)

[17] F.X.Vialard, R. Kwitt, S. Wei, M. Niethammer: A Shooting Formulation of Deep Learning. NeurIPS  2020 (ERA CORE A*)

[16] J.Y. Ahn, S. Fuchs, R. Oh: A copula transformation in multivariate mixed discrete-continuous models. Fuzzy Sets and Systems (2020)

[15]  M.R. Berthold, C. Borgelt, F. Höppner, F. Klawonn,  R. Silipo: Guide to Intelligent Data Science (2nd edition). Springer-Verlag, Berlin, Germany 2020, ISBN 978-3-030-45574-3. https://doi:10.1007/978-3-030-45574-3

[14] S. Fuchs and K.D. Schmidt: On order statistics and Kendall’s tau for copulas. Statistics and Probability Letters (2021)

[13] J. Fernández Sánchez, J.B. Seoane-Sepúlveda, W. Trutschnig: Lineability, algebrability, and sequences of random variables. To appear in Mathematische Nachrichten (2020) preprint (pdf)

[12] J. Fernández Sánchez, D.L. Rodríguez-Vidanes, J.B. Seoane-Sepúlveda, W. Trutschnig: Lineability, differentiable functions and special derivatives.  Banach Journal of Mathematical Analysis (2020)

[11] M. Wagner, , A.C. BathkeS.C. Cary, T.G.A. Green, R.R. Junker, W. Trutschnig, U. Ruprecht: Myco- and photobiont associations in crustose lichens in the McMurdo Dry Valleys (Antarctica) reveal high differentiation along an elevational gradient. Polar Biology (2020)

[10] A.S. Berghoff, M. Gansterer, A.C. Bathke, W. Trutschnig, P. Hungerländer, J.M.Berger, J. Kreminger, A.M. Starzer, R. Strassl, R. Schmid, H. Willschke, W. Lamm, M. Raderer, A.D. Gottlieb, N. J. Mauser, M. Preusser: SARS-CoV-2 Testing in Patients With Cancer Treated at a Tertiary Care Hospital During the COVID-19 Pandemic. Journal of Clinical Onkology (2020)

[9] E. Hidalgo-Lopez, G. Zimmermann, B. Pletzer: Intra-subject consistency of spontaneous eye blink rate in young women across the menstrual cycle. Scientific Reports (2020)

[8] M. Happ, G. Zimmermann, E. Brunner, A. Bathke: Pseudo-Ranks: How to Calculate Them Efficiently. R. Journal of Statistical Software, CodeSnippets (2020)

[7] G. Zimmermann, E. Trinka: Accounting for individual variability in baseline seizure frequencies when planning randomized clinical trials remains challenging. Epilepsia (2020)

[6] L. Bernal-González, J. Fernández Sánchez, J.B. Seoane-Sepúlveda, W. Trutschnig: Highly tempering infinite matrices II: From divergence to convergence via Toeplitz-Silverman matrices. Revista de la Real Academia de Ciencias Exactas, Físicas y Naturales. Serie A. Matemáticas (2020)

[5] R.R. Junker, F. Griessenberger, W. Trutschnig: Estimating scale-invariant directed dependence of bivariate distributions. Computational Statistics and Data Analysis (2021)

[4] J. Fernández Sánchez, D.L. Rodríguez-Vidanes, J.B. Seoane-Sepúlveda, W. Trutschnig: Lineability and integrability in the sense of Riemann, Lebesgue, Denjoy, and Khintchine.  Journal of Mathematical Analysis and Applications (2020)

[3] C. Hofer, F. Graf, B. Rieck, M. Niethammer, R. Kwitt: Graph Filtration Learning. ICML 2020 (CORE: A*),

[2] C. Hofer, F. Graf, M. Niethammer, R. Kwitt: Topologically Densified Distributions. ICML 2020 (CORE: A*),

[1] C. Borgelt, O. Yarikova: Initializing k-Means Clustering. International Conference on Data Science, Technology and Applications (DATA) 2020,




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