| Introduction to Neural Networks R Kruse, C Borgelt, C Braune, S Mostaghim, M Steinbrecher Computational Intelligence, 9-13, 2016 | 1526* | 2016 |
| Computational intelligence: a methodological introduction R Kruse, C Borgelt, C Braune, S Mostaghim, M Steinbrecher Springer, 2016 | 708* | 2016 |
| Computational Intelligence: Eine methodische Einführung in Künstliche Neuronale Netze, Evolutionäre Algorithmen, Fuzzy-Systeme und Bayes-Netze R Kruse, C Borgelt, C Braune, F Klawonn, C Moewes, M Steinbrecher Springer-Verlag, 2015 | 708* | 2015 |
| Multi-layer perceptrons R Kruse, S Mostaghim, C Borgelt, C Braune, M Steinbrecher Computational intelligence: a methodological introduction, 53-124, 2022 | 132 | 2022 |
| Density Based Clustering: Alternatives to DBSCAN C Braune, S Besecke, R Kruse Partitional Clustering Algorithms, 193-213, 2015 | 31 | 2015 |
| An alternating optimization approach based on hierarchical adaptations of dbscan A Dockhorn, C Braune, R Kruse 2015 IEEE Symposium Series on Computational Intelligence, 749-755, 2015 | 23 | 2015 |
| Computational Intelligence, Texts in Computer Science R Kruse, C Borgelt, C Braune, S Mostaghim, M Steinbrecher Springer London, London, 2016 | 17 | 2016 |
| Variable density based clustering A Dockhorn, C Braune, R Kruse Computational Intelligence (SSCI), 2016 IEEE Symposium Series on, 1-8, 2016 | 14 | 2016 |
| Unsicheres und vages Wissen C Borgelt, C Braune, H Timm, R Kruse Handbuch der Künstlichen Intelligenz, 235-296, 2013 | 14 | 2013 |
| New algorithms for finding approximate frequent item sets C Borgelt, C Braune, T Kötter, S Grün Soft Computing-A Fusion of Foundations, Methodologies and Applications 16 (5 …, 2012 | 13 | 2012 |
| Advanced Analysis of Dynamic Graphs in Social and Neural Networks P Held, C Moewes, C Braune, R Kruse, B Sabel Towards Advanced Data Analysis by Combining Soft Computing and Statistics …, 0 | 10 | |
| Handling Noise and Outliers in Fuzzy Clustering C Borgelt, C Braune, MJ Lesot, R Kruse Fifty Years of Fuzzy Logic and its Applications, 315-335, 2015 | 8 | 2015 |
| Radial basis function networks R Kruse, C Borgelt, C Braune, S Mostaghim, M Steinbrecher Computational Intelligence, 93-112, 2016 | 7* | 2016 |
| Using a multiobjective genetic algorithm for curve approximation T Sabsch, C Braune, A Dockhorn, R Kruse 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-6, 2017 | 6 | 2017 |
| Obtaining shape descriptors from a concave hull-based clustering algorithm C Braune, M Dankel, R Kruse Advances in Intelligent Data Analysis XV: 15th International Symposium, IDA …, 2016 | 6 | 2016 |
| Behavioral Clustering for Point Processes C Braune, C Borgelt, R Kruse Advances in Intelligent Data Analysis XII, 127-137, 2013 | 6 | 2013 |
| Multilayer perceptrons R Kruse, C Borgelt, C Braune, S Mostaghim, M Steinbrecher Computational Intelligence, 47-92, 2016 | 5 | 2016 |
| Introduction to Computational Intelligence R Kruse, C Borgelt, C Braune, S Mostaghim, M Steinbrecher, R Kruse, ... Computational Intelligence: A Methodological Introduction, 1-5, 2016 | 5 | 2016 |
| Assembly Detection in Continuous Neural Spike Train Data C Braune, C Borgelt, S Grün Advances in Intelligent Data Analysis XI, 78-89, 2012 | 5 | 2012 |
| Finding Ensembles of Neurons in Spike Trains by Non-linear Mapping and Statistical Testing C Braune, C Borgelt, S Grün Advances in Intelligent Data Analysis X, 55-66, 2011 | 5 | 2011 |
Christian BorgeltProfessor for Data Science, Paris Lodron University of SalzburgVerified email at borgelt.net
