Publikationen des IDA Labs seit Projektbeginn (März 2020)

[110] Ansari, J., Lütkebohmert, E., Neufeld, A., Sester, J.: Improved robust price bounds for multiasset derivatives under market-implied dependence information. Finance and Stochastics (2024) 

[109] Santamaría, A., Xu, C., Scomparin, L., Hirländer, S., Pochaba, S., Eichler, A., Kaiser, J., Schenk, M.: The Reinforcerment Learning for Autonomous Accelerators Collaboration. 15th International Particle Accelerator Conference,Nashville, TN (2024)

[108] Hirländer, S., Appel, S., Madysa, N.: Data-Driven model predictive control for automated optimitization of injection into the SIS18 synchrotron. 15th International Particle Accelerator Conference,Nashville, TN (2024)

[107] Hirländer, S., Lamminger, L., Pochaba, S., Kaiser, J., Xu, C., Santamaría, A., Scomparin, L., Kain, V.: Towards few-shot reinforcement learning in particle accelerator control. 15th International Particle Accelerator Conference,Nashville, TN (2024)

[106] Geroldinger, M., Verbeeck, J., Hooker, A.C., Thiel, K.E., Molenberghs, G., Nyberg, J., Bauer, J., Laimer, M., Wally, V., Bathke, A.C., Zimmermann, G.: Statistical recommendations for count, binary, and ordinal data in rare disease cross-over trials. Orphanet J Rare Dis (2023)

[105] Fuchs, S.: Quantifying directed dependence via dimension reduction. Journal of Multivariate Analysis (2024)

[104] Fuchs, S. and Tschimpke, M.: A novel positive dependence property and its impact on a popular class of concordance measures. Journal of Multivariate Analysis (2024)

[103] Kozlica, R., Schäfer, G., Hirländer, S., Wegenkittl, S.: A Modular Test Bed for Reinforcement Learning Incorporation into Industrial Applications. iDSC 2023: Data Science—Analytics and Applications (2024)

[102] Kasper, T., Dietrich, N. P.,  Trutschnig, W.: On convergence and mass distributions of multivariate Archimedean copulas and their interplay with the Williamson transform. Journal of Mathematical Analysis and Applications (2024)

[101] Ansari, J., Shushi, T., Vanduffel, S.: Up- and down-correlations in normal variance mixture models. Statistics & Probability Letters (2024)

[100] Kartal, O., Lindlbauer, N., Laner-Plamberger, S., Rohde, E., Föttinger, F., Ombres, L., Zimmermann, G., Mrazek, C., Lauth, W., Grabmer, C.: Collection efficiency of mononuclear cells in offline extracorporeal photopheresis: can processing time be shortened?  Blood transfusion (2023)

[99] Verbeeck, J.,  Geroldinger, M., Thiel, K., […], Zimmermann, G.: How to analyze continuous and discrete repeated measures in small sample cross-over trials? Biometrics (2023)

[98] Moser, T, Zimmermann, G., et al.: Long-term outcome of natalizumab-associated progressive multifocal leukoencephalopathy in Austria: a nationwide retrospective study. J Neurol (2023)

[97] Hanusch, M., He, X., Janssen, S., Selke, J., Trutschnig, W., Junker, R.R.: Exploring the Frequency and Distribution of Ecological Non-monotonicity in Associations among Ecosystem Constituents. Ecosystems (2023)

[96] Fernández Sánchez, J., López-Salazar Codes, J., Seoane-Sepúlveda, J. B. & Trutschnig, W.: Generalized Notions of Continued Fractions Ergodicity and Number Theoretic Applications. New York: Chapman And Hall (2023)

[95] Fernández Sánchez, J., Trutschnig, W.: A link between Kendall’s τ , the length measure andthe surface of bivariate copulas, and a consequence to copulas with self-similar support. Dependence Modeling (2023)

[94] Kozlica, R., Wegenkittl, S., Hirländer, S.: Deep Q-Learning versus Proximal Policy Optimization: Performance Comparison in a Material Sorting Task. in 2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE) (2023)

[93] Oeftiger, A., Garcia, S., Lagrange, J., Hirländer, S.: Active Deep Learning for Nonlinear Optics Design of a Vertical FFA Accelerato. in Proc. IPAC’23, in IPAC’23 – 14th International Particle Accelerator Conference (2023)

[92] Hirländer, S., Lamminger, L., Zevi-Della-Porta, G., V. Kain: Ultra fast reinforcement learning in accelerator control demonstrated on CERN AWAKE. in IPAC’23 – 14th International Particle Accelerator Conference (2023)

[91] Senker, H. Stefanits, S. Aspalter, W. Trutschnig, J. Franke, A. Gruber: Nonsteroidal anti-inflammatory drugs (NSAID) do not increase blood loss or the incidence of postoperative epidural hematomas when using minimally invasive fusion techniques in the degenerative lumbar spine.  Frontiers in Surgery (2022)

[90] T[]. Kasper, N. Dietrich, W. Trutschnig: On convergence and mass distributions of multivariate Archimedean copulas and their interplay with the Williamson transform.  Journal of Mathematical Analysis and Applications (2023)

[89] J. Fernández-Sánchez, J. López-Salazar Codes, J.B. Seoane Sepúlveda, W. Trutschnig: Generalized Notions of Continued Fractions: Ergodicity and Number Theoretic Applications (1st ed.). Chapman and Hall/CRC (2023)   

[88] A.M. Wiesinger, B. Bigger, R. Giugliani, C. Lampe, M. Scarpa, T. Moser, C. Kampmann, G. Zimmermann, F.B. Lagler: An Innovative Tool for Evidence-Based, Personalized Treatment Trials in Mucopolysaccharidosis. Pharmaceutics (2023) 

[87] F.M. Velotti, B. Goddard, V. Kain, R. Ramjiawan, G. Zevi Della Porta, S. Hirländer: Towards automatic setup of 18 MeV electron beamline using machine learning. Mach. Learn.: Sci. Technol. (2023)

[86] E. Trinka, L.J. Rainer, C.A. Granbichler, G. Zimmermann, M. Leitinger: Mortality, and life expectancy in Epilepsy and Status epilepticus — current trends and future aspects. Front Epidemiol (2023)  

[85] M. Geroldinger, J. Verbeeck, K.E. Thiel, G. Molenberghs, A.C. Bathke, M. Laimer, G. Zimmermann: A neutral comparison of statistical methods for analyzing longitudinally measured ordinal outcomes in rare diseases. Biom J. (2023)

[84] F. Schöpflin, S. Erber, D. Madlener, T. Prinz: Densification of Single and Two-Family Houses considering Green Space and Mobility. Acta Polytechnica CTU Proceedings (2022)

[83] G. Schäfer, R. Kozlica, S. Wegenkittl, S.Huber: An Architecture for Deploying Reinforcement Learning in Industrial Environments. In: R. Moreno-Díaz, F. Pichler, A. Quesada-Arencibia (eds) Computer Aided Systems Theory – EUROCAST 2022 (2022)

[82] S. Fuchs and M. Tschimpke: Total positivity of copulas from a Markov kernel perspective. Journal of Mathematical Analysis and Applications (2022)

[81] M. Genitrini, J. Fritz, G. Zimmermann, H. Schwameder: Downhill Sections Are Crucial for Performance in Trail Running Ultramarathons-A Pacing Strategy Analysis. J Funct Morphol Kinesiol. (2022)

[80] S. Laner-Plamberger S, […], W. Lauth, G. Zimmermann, et al.: SARS-CoV-2 IgG Levels Allow Predicting the Optimal Time Span of Convalescent Plasma Donor Suitability. Diagnostics (2022)

[79] T. Kasper, W. Trutschnig: A Markov Kernel Approach to Multivariate Archimedean Copulas. In L.A. García-Escudero et al. (Eds.), Building Bridges between Soft and Statistical Methodologies for Data Science (2022)

[78] N.P. Dietrich, J. Fernández Sánchez, W. Trutschnig: Convergence of Copulas Revisited: Different Notions of Convergence and Their Interrelations. In L.A. García-Escudero et al. (Eds.), Building Bridges between Soft and Statistical Methodologies for Data Science (2022)

[77] M. Pallauf, F. Steinkohl, G. Zimmermann, et al.: External validation of two mpMRI-risk calculators predicting risk of prostate cancer before biopsy. World Journal of Urology (2022)

[76] W. Trutschnig, F. Griessenberger: On Quantifying and Estimating Directed Dependence. In L.A. García-Escudero et al. (Eds.), Building Bridges between Soft and Statistical Methodologies for Data Science (2022)

[75] L. Machegger […], T. Prüwasser, G. Zimmermann et al.: Quantitative Analysis of Diffusion-Restricted Lesions in a Differential Diagnosis of Status Epilepticus and Acute Ischemic Stroke. Front Neurol. (2022)

[74] F. Griessenberger, W. Trutschnig: qad: An R-package to detect asymmetric and directed dependence in bivariate samples. Methods in Ecology and Evolution (2022)

[73] F.M. Velotti, B. Goddard, V. Kain, R. Ramjiawan, G.Z.D. Porta, S. Hirländer: Automatic setup of 18 MeV electron beamline using machine learning. InProceedings (Velotti2022AutomaticSO) (2022)

[72] F. Griessenberger, W. Trutschnig: Maximal asymmetry of bivariate copulas and consequences to measures of dependence. Dependence Modeling (2022)

[71] V. Kain, N. Bruchon, S. Hirländer, N. Madysa,  I. Vojskovic, P.K. Skowronski, G. Valentino: Test of Machine Learning at the Cern LINAC4. InProceedings (Kain2022TESTOM) (2022)

[70] S. Fuchs: The simplifying assumption in pair-copula constructions from an analytic perspective. In L.A. García-Escudero et al. (Eds.), Building Bridges between Soft and Statistical Methodologies for Data Science (2022)

[69] Á.K. Csete, A. Kovács-Győri, P. Szilassi: Age-group-based evaluation of residents’ urban green space provision: Szeged, Hungary. A case study. Hungarian Geographical Bulletin (2022)

[68] L. Grech, G. Valentino, D. Alves, S. Hirländer: Application of reinforcement learning in the LHC tune feedback. Frontiers in Physics (2022)

[67] M. Happ, J.L. Du, M. Herlich, C. Maier, P. Dorfinger, J. Suárez-Varela: Exploring the Limitations of Current Graph Neural Networks for Network Modeling. In: Proceedings of the IEEE/IFIP Network Operations and Management Symposium. (2022)

[66] S. Fuchs, M. Tschimpke:. On positive dependence properties for Archimedean copulas. In L.A. García-Escudero et al. (Eds.), Building Bridges between Soft and Statistical Methodologies for Data Science (2022)

[65] T. Mroz, J. Fernández Sánchez, S. Fuchs, W. Trutschnig: On distributions with fixed marginals maximizing the joint or the prior default probability, estimation, and related results. Journal of Statistical Planning and Inference (2022)

[64] C. Ferner: Captioning Bosch: A Twitter Bot. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22 (2022)

[63] C. Ferner, S. Wegenkittl: Benefits from Variational Regularization in Language Models. Machine Learning & Knowledge Extraction (2022)

[62] L.J. Rainer, M. Kronbichler, G. Kuchukhidze, E. Trinka, P.B. Langthaler, L. Kronbichler, S. Said-Yuerekli, M. Kirschner, G. Zimmermann, J. Höfler, E. Schmid, M. Braun: Emotional Word Processing in Patients With Juvenile Myoclonic Epilepsy. Front Neurol. (2022)

[61] J. Carmona Tapia, J. Fernández Sánchez, J.B. Seoane-Sepúlveda, W. Trutschnig: Lineability, Spaceability, and Latticeability of subsets of C([0,1]) and Sobolev Spaces. Revista de la Real Academia de Ciencias Exactas, Físicas y Naturales. Serie A. Matemáticas (2022), 

[60] M.J. Mair, J.M. Berger, M. Mitterer, P. Gattinger, J.M. Berger, W. Trutschnig, A.C. Bathke, et al.: Enhanced SARS-CoV-2 breakthrough infections in patients with hematologic and solid cancers due to Omicron. Cancer Cell (2022)

[59] F. Griessenberger, R.R. Junker, W. Trutschnig: On a multivariate copula-based dependence measure and its estimation. Electronic Journal of Statistics (2022), 

[58] V. Nunhofer, L. Weidner, A.D. Hoeggerl, G. Zimmermann, et al.: Persistence of Naturally Acquired and Functional SARS-CoV-2 Antibodies in Blood Donors One Year after Infection. Viruses (2022)

[57] F. Petersen, C. Borgelt, H. Kuehne, O. Deussen: Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision. Proc. 38th Int. Conf. on Machine Learning (ICML 2021) PMLR Proceedings (2021),,

[56] F. Petersen, C. Borgelt, H. Kuehne, O. Deussen: GenDR: A Generalized Differentiable Renderer. Proc. Int. Conf. on Computer Vision and Pattern Recognition (CVPR 2022, New Orleans, LA, USA) (2021),,

[55] F. Petersen, C. Borgelt, H. Kuehne, O. Deussen: Monotonic Differentiable Sorting Networks. Proc. 10th Int. Conf. on Learning Representations (ICLR 2022, virtual) (2021),

[54] K. Aleksovska, T. Kobulashvili, J. Costa, G. Zimmermann, et al.:  European Academy of Neurology guidance for developing and reporting clinical practice guidelines on rare neurological diseases. European Journal of Neurology (2022)

[53] J. Fernández-Sánchez,  J.B. Seoane-Sepúlveda, W. Trutschnig: Lineability, algebrability, and sequences of random variables. Mathematische Nachrichten (2022)

[52] S. Roesch, A. O’Sullivan, G. Zimmermann,  A. Mair, C. Lipuš, J.A. Mayr, S.B. Wortmann and G. Rasp: Mitochondrial Disease and Hearing Loss in Children: A Systematic ReviewThe Laryngoscope (2022)

[51] M.J. Mair, J.M. Berger, M. Mitterer, M. Gansterer, A.C. Bathke, W. Trutschnig, A. S. Berghoff, T. Perkmann, H. Haslacher, W.W. Lamm, M. Raderer, S. Tobudic, T. Fuereder, T. Buratti, D. Fong, M. Preusser: Third dose of SARS-CoV-2 vaccination in hemato-oncological patients and health care workers: immune responses and adverse events – a retrospective cohort study. European Journal of Cancer (2022)

[50] F. Petersen, C. Borgelt, H. Kuehne, O. Deussen: Learning with Algorithmic Supervision via Continuous Relaxations2. Proc. Neural Information Processing Systems 34 (NeurIPS 2021) (2021),,

[49] F. Petersen, C. Borgelt, H. Kuehne, O. Deussen: Learning with Algorithmic Supervision via Continuous Relaxation. Proc. Neural Information Processing Systems 34 (NeurIPS 2021) (2021)

[48] V. Racher, C. Borgelt: Gradient Ascent for Best Response Regression. Proc. 19th Int. Symposium on Intelligent Data Analysis  (IDA 2021, Porto, Portugal) (2021)

[47] A. Astner-Rohracher, G. Zimmermann, T. Avigdor, et al.: Development and Validation of the 5-SENSE Score to Predict Focality of the Seizure-Onset Zone as Assessed by Stereoelectroencephalography. JAMA Neurol. (2021)

[46] M. Wagner, G. Brunauer, A.C. Bathke, S.C. Cary, R. Fuchs, L.G. Sancho, R. Türk, U. Ruprecht: Macroclimatic conditions as main drivers for symbiotic association patterns in lecideoid lichens along the Transantarctic Mountains, Ross Sea region, AntarcticaScientific Reports (2021)

[45] G. Zimmermann, E. Brunner, W. Brannath, M. HappA.C. Bathke: Pseudo-Ranks: The Better Way of Ranking? The American Statistician (2021)

[44] A. Egger-Rainer, S.M. Hettegger, R. Feldner, S. Arnold, C. Bosselmann, H. Hamer, A. Hengsberger, J. Lang, S. Lorenzl, H. Lerche, S. Noachtar, E. Pataraia, A. Schulze-Bonhage, A.M. Staack, E. Trinka, I. Unterberger, G. Zimmermann: Do all patients in the epilepsy monitoring unit experience the same level of comfort? A quantitative exploratory secondary analysis. J Adv Nurs. (2021)

[43]  E. Gfrerer, D. Laina, G. Danae, M. Gibernau, R. Fuchs, M. Happ, T. Tolasch, W. Trutschnig, A.C. Hörger, H.P. Comes, S. Dötterl: Floral scents of a deceptive plant are hyperdiverse and under population-specific phenotypic selection. Frontiers in Plant Science (2021)

[42] W. Senker, H. Stefanits, M. Gmeiner, W. Trutschnig, C. Radl, A. Gruber: The Influence of Smoking in Minimally Invasive Spinal Fusion Surgery. Open Medicine (2021)

[41] F. Kröger, G. Weber, S. Hirländer, R. Alemany–Fernández, M. W. Krasny, T. Stohlker, I. Tolstikhina, V. Shevelko: Charge-state distributions of highly charged lead ions at relativistic collision energies. Annalen der Physik (2021)

[40] N. Bruchon, G. Fenu, G. Gaio, S. Hirländer, M. Lonza, F.A. Pellegrino, E. Salvato: An Online Iterative Linear Quadratic Approach for a Satisfactory Working Point Attainment at FERMI. Information (2021)

[39] T. Kovács, A. Kovacs-Györi, B. Resch: #AllforJan: How Twitter Users in Europe Reacted to the Murder of Ján Kuciak—Revealing Spatiotemporal Patterns through Sentiment Analysis and Topic Modeling. International Journal of Geo-Information (2021)

[38] J. Suárez-Varela, M. Ferriol-Galmés, A. López, P. Almasan, G. Bernárdez , D. Pujol-Perich, K. Rusek, L. Bonniot, C. Neumann, F. Schnitzler, F. Taïani, M. HappC. Maier, J. Lei Du, M. Herlich, P. Dorfinger, N.V. Hainke, S. Venz, J. Wegener, H. Wissing, B. Wu, S. Xiao, P. Barlet-Ros, A. Cabellos-Aparicio: The Graph Neural Networking Challenge: A Worldwide Competition for Education in AI/ML for Networks. ACM SIGCOMM Computer Communication Review (2021)

[37] T. Kasper, S. Fuchs, W. Trutschnig: On convergence of associative copulas and related results. Dependence Modeling (2021),

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

[35] F. Konietschke, C. Cao, A. Gunawardana, G. Zimmermann: Analysis of covariance under variance heteroscedasticity in general factorial designs. Stat Med. (2021),

[34] L. Weidner, V. Nunhofer, C. Jungbauer, A.D. Hoeggerl, L. Grüner, C. Grabmer, G. Zimmermann, E. Rohde, S. Laner-Plamberger: Seroprevalence of anti-SARS-CoV-2 total antibody is higher in younger Austrian blood donors. Infection (2021)

[33] T. Kasper, S. FuchsW. Trutschnig: On weak conditional convergence of bivariate Archimedean and Extreme Value copulas, and consequences to nonparametric estimation. Bernoulli (2021)

[32] M. Happ, M Herrlich, C. Maier, J. L. Du, P. Dorfinger: Graph‑neural‑network‑based delay estimation for communication networkswith heterogeneous scheduling policies. ITU Journal on Future and Evolving Technologies (2021)  ISSN: 2616-8375

[31] A. Kovacs-Györi, B. Resch: Towards an automated spatial workflow for the global monitoring of public urban green accessibility in the light of the sustainable development goals.  gis.Science 2 (2021)

[30] 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. (2021)

[29] 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)

[28] T. Mroz, S. FuchsW. 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)

[27] A.C. BathkeM. Happ, M. Hummer: Indirekte Impfeffekte für Kinder und Jugendliche bei Durchimpfung der Erwachsenen. Vergleichende Fallstudie Schwaz / Tirol, Stand 24.05.2021.  Executive Policy Brief (2021)

[26] 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)

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

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

[23] 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)

[22] 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)

[21] C. Borgelt: Even Faster Exact k-Means Clustering. Proc. 18th Int. Symp. on Intelligent Data Analysis (IDA 2020, Konstanz, Germany) (2020),,

[20] 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)

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

[18] 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)

[17] 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)

[16] S. FuchsW. Trutschnig: On quantile-based co-risk measures and their estimation. Dependence Modeling (2020)

[15] 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)

[14] 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)

[13] 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)

[12] 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)

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

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

[9]  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

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

[7] 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)

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

[5] A.S. Berghoff, M. Gansterer, A.C. BathkeW. 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)

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

[3] 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)

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

[1] 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)