DeepBionics


Publications

2018:

Thrun, M. C. : Projection-Based Clustering through Self-Organization and Swarm Intelligence, Springer, Heidelberg, ISBN: 978-3658205393, 2018.

Thrun, M. C. : Cluster Analysis of the World Gross-Domestic Product Based on Emergent Self-Organization of a Swarm, in Papież, M. & Śmiech, S. (eds.), Proc. 12th Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena, pp. 523-532, Foundation of the Cracow University of Economics, Cracow, Poland, 2018.

Thrun, M. C., & Ultsch, A. : Effects of the payout system of income taxes to municipalities in Germany, in Papież, M. & Śmiech, S. (eds.), Proc. 12th Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena, pp. 533-542, Cracow: Foundation of the Cracow University of Economics, Cracow, Poland, 2018.

Thrun, M. C., Breuer, L., & Ultsch, A. : Knowledge discovery from low-frequency stream nitrate concentrations: hydrology and biology contributions, Proc. European Conference on Data Analysis (ECDA), pp. 46-47, Paderborn, Germany, 2018.

Thrun, M. C., Pape, F., & Ultsch, A. : Benchmarking Cluster Analysis Methods using PDE-Optimized Violin Plots, Proc. European Conference on Data Analysis (ECDA) pp. 26, Paderborn, Germany, 2018.

Thrun, M. C., & Ultsch, A. : Investigating Quality measurements of projections for the Evaluation of Distance and Density-based Structures of High-Dimensional Data, Proc. European Conference on Data Analysis (ECDA), pp. 45-46, Paderborn, Germany, 2018.

Weyer-Menkhoff, I., Thrun, M. C., & Lötsch, J. : Machine-learned analysis of quantitative sensory testing responses to noxious cold stimulation in healthy subjects, European Journal of Pain, Vol. 22(5), pp. 862-874, DOI: 10.1002/ejp.1173, 2018.

Kringel, D., Geisslinger, G., Resch, E., Oertel, B. G., Thrun, M. C., Heinemann, S., & Lötsch, J. : Machine-learned analysis of the association of next-generation sequencing based human TRPV1 and TRPA1 genotypes with the sensitivity to heat stimuli and topically applied capsaicin, Pain, Vol. 159(7), pp.1366-1381, doi 10.1097/j.pain.0000000000001222, 2018

2017:

Ultsch, A., & Thrun, M. C. : Credible Visualizations for Planar Projections, in Cottrell, M. (Ed.), 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM), 10.1109/WSOM.2017.8020010, pp. 1-5, IEEE, Nany, France, 2017.

Thrun, M. C., & Ultsch, A. : Projection based Clustering, Proc. International Federation of Classification Societies (IFCS), pp. 250-251, Japanese Classification Society (JCS), Tokyo, Japan, 2017.

Thrun, M. C., & Ultsch, A. : Swarm Intelligence for Self-Organized Clustering, Journal of Artificial Intelligence, under revison, 2017.

Lötsch, J., Thrun, M. C., Lerch, F., Brunkhorst, R., Schiffmann, S., Thomas, D., . . . Ultsch, A. : Machine-learned data structures of lipid marker serum concentrations in multiple sclerosis patients differ from those in healthy subjects, International journal of molecular sciences, Vol. 18(6), pp. 1217. doi doi:10.3390/ijms18061217, 2017.

2016:

Aubert, A. H., Thrun, M. C., Breuer, L., & Ultsch, A. : Knowledge discovery from high-frequency stream nitrate concentrations: hydrology and biology contributions, Scientific reports, Nature, Vol. 6(31536), pp. doi 10.1038/srep31536, 2016.

Thrun, M. C., Lerch, F., Lötsch, J., & Ultsch, A. : Visualization and 3D Printing of Multivariate Data of Biomarkers, in Skala, V. (Ed.), International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG), Vol. 24, Plzen, 2016.

2014-2015:

Thrun, M. C., & Ultsch, A. : Models of Income Distributions for Knowledge Discovery, Proc. European Conference on Data Analysis (ECDA), DOI: 10.13140/RG.2.1.4463.0244, pp. 136-137, Colchester, 2015.

Ultsch, A., Thrun, M. C., Hansen-Goos, O., & Lötsch, J. : Identification of Molecular Fingerprints in Human Heat Pain Thresholds by Use of an Interactive Mixture Model R Toolbox (AdaptGauss), International journal of molecular sciences, Vol. 16(10), pp. 25897-25911, 2015.

Stoll, J., Thrun, M. C., Nuthmann, A., & Einhäuser, W. : Overt attention in natural scenes: objects dominate features, Vision research, Vol. 107, pp. 36-48, 2015.

Marx, S., Hansen-Goos, O., Thrun, M. C., & Einhäuser, W. : Rapid serial processing of natural scenes: Color modulates detection but neither recognition nor the attentional blink, Journal of vision, Vol. 14(14), DOI:10.1167/14.14.4, 2014.

Acknowledgments:

Lötsch, J., Lerch, F., Djaldetti, R., Teqeder, I., Ultsch, A. : Identification of disease-distinct complex biomarker patterns by means of unsupervised machine-learning using an interactive R toolbox (Umatrix), BMC Big Data Analytics, pp. 1-17, 2018.

Ultsch, A., Lötsch, J. : Computed ABC analysis for rational selection of most informative variables in multivariate data, PloS one, Vol. 10(6), pp. 1-15, 2015.

Hart, B. M., Schmidt, H. C. E. F., Roth, C., & Einhauser, W. : Fixations on objects in natural scenes: dissociating importance from salience. Frontiers in psychology, 4(455), DOI: 10.3389/fpsyg.2013.00455, 2013.