2021
Joshua Driesen, Ziad El-Khatib, Niklas Wulkow, Mitchell Joblin, Iskriyana Vasileva, Andreas Glücker, Valentin Kruspel, Catherine Vogel	Data-Powered Positive Deviance during the SARS-CoV-2 Pandemic—An Ecological Pilot Study of German Districts	International Journal of Environmental Research and Public Health, 18(9765), pp. 1-29, 2021	BibTeX DOI
Niklas Wulkow, Péter Koltai, Vikram Sunkara, Christof Schütte	Data-driven modelling of nonlinear dynamics by polytope projections and memory	arXiv, p. 2112.06742, 2021 (under review)	BibTeX arXiv
Klaus-Dieter Hungenberg, Christian Schwede, Michael Wulkow, Niklas Wulkow	Determination of reactivity ratios for acrylic acid and its dimer from classical parameter estimation and Bayesian approach	Canadian Journal of Chemical Engineering, pp. 1-10, 2021	BibTeX DOI
Niklas Wulkow, Regina Telgmann, Klaus-Dieter Hungenberg, Christof Schütte, Michael Wulkow	Deterministic and Stochastic Parameter Estimation for Polymer Reaction Kinetics I: Theory and Simple Examples	Macromolecular Theory and Simulations, Vol.30, 2021	BibTeX DOI
Niklas Wulkow, Péter Koltai, Christof Schütte	Memory-Based Reduced Modelling and Data-Based Estimation of Opinion Spreading	Journal of Nonlinear Science, Vol.31, 2021	BibTeX DOI
2018
Natasa Djurdjevac Conrad, Daniel Fuerstenau, Ana Grabundzija, Luzie Helfmann, Martin Park, Wolfram Schier, Brigitta Schütt, Christof Schütte, Marcus Weber, Niklas Wulkow, Johannes Zonker	Mathematical modeling of the spreading of innovations in the ancient world	eTopoi. Journal for Ancient Studies, Vol.7, 2018	PDF BibTeX
2017
Niklas Wulkow	Modelling the Spread of Innovations by a Markov Process in a Bayesian Framework	Master's thesis, Freie Universität Berlin, Christof Schütte, Marcus Weber (Advisors), 2017	PDF BibTeX URN
Tim Conrad, Martin Genzel, Nada Cvetkovic, Niklas Wulkow, Alexander Benedikt Leichtle, Jan Vybiral, Gitta Kytyniok, Christof Schütte	Sparse Proteomics Analysis – a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data	BMC Bioinfomatics, 18(160), 2017	BibTeX DOI