Keywords:
- Artificial Neural Networks
- Bayesian Networks
- clustering
- Computational Intelligence
- continuous data
- dynamic graphs
- EEG
- Enron dataset
- ensemble detection
- Evolutionary Algorithms
- Fuzzy Systems
- Hebbian learning
- multidimensional scaling
- Neural Networks
- neuroimaging
- neuroscience
- point processes
- social network analysis
- spike train
- spike train analysis
Publications of Christian Borgelt sorted by recency
Memory-efficient analysis of dense functional connectomes (2016), in: Frontiers in neuroinformatics Lausanne Frontiers Research Foundation, 10 2016 12 Bd. 10.2016, Art.-Nr. 50, insges. 12 S. | , , , and ,
Computational Intelligence - A Methodological Introduction, Springer, 2016 | , , , and ,
Unsicheres und vages Wissen, in: Handbuch der Künstlichen Intelligenz, pages 235-296, De Gruyter, 2013 | , , and ,
Handling Noise and Outliers in Fuzzy Clustering, in: Fifty Years of Fuzzy Logic and its Applications, pages 315-335, Springer International Publishing, 2015 | , , and ,
Mining Frequent Parallel Episodes with Selective Participation, in: 16th World Congress of the International Fuzzy Systems Association (IFSA) 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), Atlantis Press, 2015 | , , and ,
Computational Intelligence: Eine methodische Einführung in Künstliche Neuronale Netze, Evolutionäre Algorithmen, Fuzzy-Systeme und Bayes-Netze, Springer Vieweg, 2015 | , , , , and ,
Bedeutung von Zugehörigkeitsgraden in der Fuzzy-Technologie (2015), in: Informatik-Spektrum, 38:6(490-499) | and ,
Prototype Construction for Clustering of Point Processes based on Imprecise Synchrony, in: EUSFLAT-13, Atlantis Press, 2013 | and ,
Behavioral Clustering for Point Processes, in: Advances in Intelligent Data Analysis XII, pages 127-137, Springer Berlin Heidelberg, 2013 | , and ,
Mining Local Connectivity Patterns in fMRI Data., in: Towards Advanced Data Analysis by Combining Soft Computing and Statistics, pages 305--317, Springer Berlin Heidelberg, 2013 | , and ,
Assembly Detection in Continuous Neural Spike Train Data, in: Advances in Intelligent Data Analysis XI, pages 78-89, Springer Berlin / Heidelberg, 2012 | , and ,
Computational Intelligence: A Methodological Introduction, Springer, Texts in Computer Science, 2013 | , , , , and ,
Finding Ensembles of Neurons in Spike Trains by Non-linear Mapping and Statistical Testing, in: Advances in Intelligent Data Analysis X, pages 55-66, Springer Berlin / Heidelberg, 2011 | , and ,
New Algorithms for Finding Approximate Frequent Item Sets (2012), in: Soft Computing - A Fusion of Foundations, Methodologies and Applications, 16:2(903-917) | , , and ,
Advanced Analysis of Dynamic Graphs in Social and Neural Networks, in: Towards Advanced Data Analysis by Combining Soft Computing and Statistics, pages 205--222, Springer, 2013 | , , , and ,
Computational Intelligence: Eine methodische Einführung in Künstliche Neuronale Netze, Evolutionäre Algorithmen, Fuzzy-Systeme und Bayes-Netze, Vieweg+Teubner, Computational Intelligence, 2011 | , , , , and ,
Constraining Shape and Size in Clustering, in: Cooperation in Classification and Data Analysis, pages 13--25, Springer, 2009 | and ,
Graphical Models: Representations for Learning, Reasoning and Data Mining, Wiley, 2009 | , and ,
An Extended Objective Function for Prototype-less Fuzzy Clustering, in: Proc. Conf. North American Fuzzy Information Processing Society (NAFIPS 2007), pages 146--151, 2007 | and ,
The role of soft computing in intelligent data analysis, in: Final program and abstracts of the 2007 IEEE International Conference on Fuzzy Systems, pages 9--17, 2007 | , , , and ,
Concepts for Probabilistic and Possibilistic Induction of Decision Trees on Real World Data, in: Proc.\ 4th European Congress on Intelligent Techniques and Soft Computing (EUFIT'96, Aachen, Germany), pages 1556--1560, Verlag Mainz, 1996 | , and ,
Probabilistic and Possibilistic Networks and How to Learn Them from Data, in: Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications, pages 403--426, Springer-Verlag, 1998 | and ,
Inference Methods, in: Handbook of Fuzzy Computation, Institute of Physics Publishing, 1998 | , and ,
Efficient Maximum Projection of Database-Induced Multivariate Possibility Distributions, in: Proc.\ 7th IEEE Int.\ Conf.\ on Fuzzy Systems (FUZZ-IEEE'98, Anchorage, AK), pages 663--668, IEEE Press, 1998 | and ,
Neuere Entwicklungen im Data Mining mit Bayesschen Netzen, in: Seminar zu Anwendungen von Fuzzy-Technologien und Neuronalen Netzen (Wernigerode, Germany), MIT GmbH, 1998 | and ,
Possibilistic Networks: Data Mining Applications, in: Proc.\ 6th European Congress on Intelligent Techniques and Soft Computing (EUFIT'98, Aachen Germany), pages 603--607, Verlag Mainz, 1998 | and ,
Possibilistic Networks with Local Structure, in: Proc.\ 6th European Congress on Intelligent Techniques and Soft Computing (EUFIT'98, Aachen, Germany), pages 634--638, Verlag Mainz, 1998 | and ,
Data Mining with Graphical Models, in: Proc.\ Computer Science for Environmental Protection (12th Int.\ Symp.\ ``Informatik für den Umweltschutz'', Bremen, Germany), pages 17--30, 1998 | and ,
Fuzzy-Methoden in der Datenanalyse, in: {F}uzzy-{T}heorie und {S}tochastik, pages 370--386, Vieweg, 1999 | , and ,
A Critique of Inductive Causation, in: Proc. 5th European Conf. on Symbolic and Quantitative Approaches to Reasoning and Uncertainty (ECSQARU'99, London, United Kingdom), pages 68--79, Springer-Verlag, 1999 | and ,
Fuzzy Data Analysis: Challenges and Perspectives, in: Proceedings of the 8th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE '99, Seoul, South Korea), pages 1211--1216, IEEE Press, 1999 | , and ,
Data Mining mit Neuro-Fuzzy-Systemen, in: Proc.\ Symposium Operations Research (SOR'99, Magdeburg, Germany), 1999 | , and ,
Data Mining with Fuzzy Methods: Status and Perspectives, in: Proc.\ 7th European Congress on Intelligent Techniques and Soft Computing (EUFIT'99, Aachen, Germany), Verlag Mainz, 1999 | , and ,
Abductive Inference with Probabilistic Networks, in: Abductive Reasoning and Learning, Kluwer, 2000 | and ,
Using Fuzzy Clustering to Improve Naive Bayes Classifiers and Probabilistic Networks, in: Proc.\ 9th IEEE Int.\ Conf.\ on Fuzzy Systems (FUZZ-IEEE'00, San Antonio, TX), IEEE Press, 2000 | , and ,
Unsicheres und vages Wissen, in: Einführung in die Künstliche Intelligenz (3.~Auflage), pages 291--347, Addison-Wesley, 2000 | , and ,
Possibilistic Graphical Models, in: Computational Intelligence in Data Mining (Proc.\ 3rd Int.\ Workshop, Udine, Italy), pages 51--68, Springer-Verlag, 2000 | , and ,
Problems and Prospects in Fuzzy Data Analysis, in: Soft Computing and Intelligent Systems: Prospects, Tools and Applications, pages 95--109, Springer-Verlag, 2000 | , and ,
Learning from Imprecise Data: Possibilistic Graphical Models, in: Proc.\ Int.\ Meeting on Nonlinear Methods and Data Mining (NMDM 2000), pages 190--203, Consiglio Nazionale delle Ricerche, 2000 | and ,
Probabilistic Networks and Fuzzy Clustering as Generalizations of Naive Bayes Classifiers, in: Computational Intelligence in Theory and Practice, pages 121--138, Physica-Verlag, 2001 | , and ,
Unsicherheit und Vagheit: Begriffe, Methoden, Forschungsthemen (2001), in: {K}ünstliche Intelligenz, {T}hemenheft Unsicherheit und {V}agheit, 15:3(5--8) | and ,
An Empirical Investigation of the K2 Metric, in: Proc.\ 6th European Conf.\ on Symbolic and Quantitative Approaches to Reasoning and Uncertainty (ECSQARU'01, Toulouse, France), pages 240--251, Springer-Verlag, 2001 | and ,