Prof. Dr. Thomas Kneib

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  • 2017 | Journal Article | 
    ​ ​Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies​
    Friedrichs, S. ; Manitz, J. ; Burger, P.; Amos, C. I.; Risch, A.; Chang-Claude, J. & Wichmann, H.-E. et al.​ (2017) 
    Computational and mathematical methods in medicine, 2017 pp. 6742763​-17​.​ DOI: https://doi.org/10.1155/2017/6742763 
    ​Details  DOI  PMID  PMC 
  • 2015 | Journal Article | 
    ​ ​Assessing opportunities for physical activity in the built environment of children: interrelation between kernel density and neighborhood scale​
    Buck, C.; Kneib, T. ; Tkaczick, T.; Konstabel, K. & Pigeot, I.​ (2015) 
    International Journal of Health Geographics, 14(1).​ DOI: https://doi.org/10.1186/s12942-015-0027-3 
    ​Details  DOI 
  • 2013 | Review | 
    ​ ​Gerhard Tutz: „Regression for Categorical Data“​
    Kneib, T. ​ (2013)
    Jahresbericht der Deutschen Mathematiker-Vereinigung, 115​(1) pp. 51​-55​.​ DOI: https://doi.org/10.1365/s13291-013-0058-2 
    ​Details  DOI 
  • 2011 | Journal Article | 
    ​ ​Comparison of a Bayesian and a regression model for stimulus classification​
    Köpcke, L. S; Furche, J.; Juárez Paz, L. M; Kneib, T.   & Kretzberg, J.​ (2011) 
    BMC Neuroscience, 12(S1).​ DOI: https://doi.org/10.1186/1471-2202-12-S1-P178 
    ​Details  DOI 
  • 2010 | Journal Article | 
    ​ ​Model-based Boosting 2.0​
    Hothorn, T.; Bühlmann, P.; Kneib, T. ; Schmid, M. & Hofner, B.​ (2010) 
    Journal of Machine Learning Reseach - Machine Learning Open Source Software, 11 pp. 2109​-2113​.​
    ​Details 

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