english version
Nächster Vortrag im Stochastischen Kolloquium:
20.06.2018, 11:15, Dr. Anthony Lee (University of Bristol)

"Particle filters and variance estimation" (Abstract).
Dr. Yoav Zemel, EPF Lausanne, spends SNF Early Postdoc Mobility fellowship at IMS: The IMS welcomes Dr. Yoav Zemel, who is spending with us an 18-months research visit from February 1st, 2018 to July 31st, 2019. Dr. Zemel is funded by a Swiss National Science Foundation Early Postdoc Mobility fellowship for the project Uncertainty Quantification for Optimal Transport mentored by Prof. Axel Munk (more information is available here).

Arbeitsgruppe "Angewandte und Mathematische Statistik"
Publikationen: Gesamtliste

SFB803 - Z2

  • Bartsch, A., Llabrés, S., Pein, F., Kattner, C., Schön, M., Diehn, M., Tanabe, M., Munk, A., Zachariae, U., Steinem, C. (2018).
    High-resolution experimental and computational electrophysiology reveals weak β-lactam binding events in the porin PorB. bioRxiv 303891. Submitted.
  • Behr, M., Holmes, C., Munk, A. (2018).
    Multiscale blind source separation. arXiv:1608.07173 The Annals of Statististics, 46, 711-744.
  • Pein, F., Tecuapetla-Gómez, I., Schütte, O. M., Steinem, C., Munk, A. (2017).
    Fully-Automatic Multiresolution idealization for filtered ion channel recordings: Flickering event detection arXiv:1706.03671. Submitted.
  • Gawthrop, P., Siekmann, I., Kameneva, T., Saha, S., Ibbotson, M. R. and Crampin, E. J. (2017).
    Bond Graph Modelling of Chemoelectrical Energy Transduction. Submitted.
  • Tecuapetla-Gómez, I., Munk, A. (2017).
    Autocovariance estimation in regression with a discontinuous signal and m-dependent errors: A difference-based approach (R package: dbacf). arXiv:1507.02485v4 Scandinavian Journal of Statistics, 44, 346-368.
  • Behr, M., Munk, A. (2017).
    Identifiability for blind source separation of multiple finite alphabet linear mixtures. arXiv:1505.05272 IEEE Trans. Inf. Theory, 63, 5506 - 5517.
  • Pein, F., Sieling, H., Munk, A. (2017).
    Heterogeneuous change point inference (R package: HSMUCE). arXiv:1505.04898 Journ. Royal. Statist. Soc. Ser. B, 79, 1207–1227.
  • Siekmann, I., Fackrell, M., Taylor, P. and Crampin, E. J. (2016).
    Modelling modal gating in ion channels with hierarchical Markov models. Proceedings of the Royal Society of London A, 472, 20160122.
  • Siekmann, I. and Malchow, H. (2016).
    Fighting Enemies and Noise: Competition of Residents and Invaders in a Stochastically Fluctuating Environment. Mathematical Modelling of Natural Phenomena (MMNP), 11(5), 120-140.
  • Hafi, N., Grunwald, M., van den Heuvel, L. S., Aspelmeier, T., Chen, J.-H., Zagrebelsky, M., Schuette, O. M., Steinem, C., Korte, M., Munk, A., Walla, J. P. (2016).
    Corrigendum: Fluorescence nanoscopy by polarization modulation and polarization angle narrowing. Nature Methods, 13, 101.
  • Hafi, N., Grunwald, M., van den Heuvel, l.S., Aspelmeier, T., Steinem, C., Korte, M., Munk, A., Walla, J.P. (2016).
    Reply to "Polarization modulation adds little additional information to super-resolution fluorescence microscopy" Nature Methods, 13, 8-9.
  • Li, H., Munk, A., Sieling, H. (2016).
    FDR-control in multiscale change-point segmentation. Electron. J. Statist., 10, 918-959.
  • Pein, F. (2015).
    HSMUCE - an R package for change-point inference for heterogeneous data.
  • Futschik, A., Hotz, T., Munk, A., Sieling, H. (2014).
    Multiscale DNA partitioning: statistical evidence for segments. Bioinformatics, doi: 10.1093/bioinformatics/btu180 (Preprint).
  • Frick, S., Hohage, T., Munk, A. (2014).
    Asymptotic laws for change point estimation in inverse regression. Statistica Sinica, 24, 555-575 (Preprint).
  • Frick, K., Munk, A., Sieling, H. (2014).
    Multiscale Change-Point Inference (software "stepR" for multiscale change point analysis "SMUCE") With discussion and rejoinder by the authors. Journ. Royal Statist. Society, Ser. B., 76, 495-580. arXiv:1301.7212 long version with full proofs.
  • Hotz,T., Schütte, O., Sieling, H., Polupanow, T., Diederichsen, U., Steinem, C., Munk, A. (2013).
    Idealizing ion channel recordings by jump segmentation and statistical multiresolution analysis IEEE Trans. on NanoBioScience, 12, 376-386. (Preprint).
  • Hotz, T., Huckemann, S., Le, H., Marron, J. S., Mattingly, J. C., Miller, E., Nolen, J., Owen, M., Patrangenaru, V., Skwerer, S. (2013).
    Sticky central limit theorems on open books. Annals of Applied Probability, 23(6) 2238-2258 , 1202.4267 [math.PR] [math.MG] [math.ST].
  • Krivobokova, T., Briones, R., Hub, J., Munk, A., de Groot, B. (2012).
    Partial least squares functional mode analysis: application to membrane proteins AQP1, Aqy1 and CLC-ec1 Biophysical Journal, 103, 786-796.
  • Frick, K., Marnitz, P., Munk, A. (2012).
    Statistical Multiresolution Dantzig Estimation in Imaging: Fundamental Concepts and Algorithmic Framework Electron. J. Stat., 6, 231-268.
  • Hotz, T., Gottschlich, C., Lorenz, R., Bernhardt, S., Hantschel, M., Munk, A. (2011).
    Statistical Analyses of Fingerprint Growth. BIOSIG 2011 - Proceedings - International Conference of the Biometrics Special Interest Group, 08.-09. September 2011 in Darmstadt, Germany. Lecture Notes in Informatics, P-191, 11-20.
  • Gottschlich, C., Hotz, T., Lorenz, R., Bernhardt, S., Hantschel, M., Munk, A. (2011).
    Modeling the Growth of Fingerprints Improves Matching for Adolescents IEEE Transactions on Information Forensics and Security, 6, 1165-1169.
  • Huckemann, S., Hotz, T., Munk, A. (2010).
    Intrinsic MANOVA for Riemannian Manifolds with an Application to Kendalls Spaces of Planar Shapes. IEEE Trans. Patt. Anal. Mach. Intell., 32, 593-603, "Spotlight Paper" for this issue with its "Special Section on Shape Analysis and its Applications in Image Understanding", freely available until 18 March 2010 (Preprint).