Some Experimental Results on Learning Probabilistic and Possibilistic Networks with Different Evaluation Measures. - Christian Borgelt; Rudolf Kruse (ECSQARU-FAPR, 1997)

Data Mining with Graphical Models. - Rudolf Kruse; Christian Borgelt (KI, 1998)

Lernen probabilistischer und possibilistischer Netze aus Daten: Theorie und Anwendung. - Christian Borgelt; Rudolf Kruse; Guido Lindner (Künstliche Intell., 1998)

Fuzzy Methoden in der Datenanalyse. - Christian Borgelt; Jörg Gebhardt; Rudolf Kruse (Fuzzy Theorie und Stochastik, 1999)

A Critique of Inductive Causation. - Christian Borgelt; Rudolf Kruse (ESCQARU, 1999)

Possibilistic Graphical Models. - Christian Borgelt; Jörg Gebhardt; Rudolf Kruse (Computational Intelligence in Data Mining, 2000)

Using fuzzy clustering to improve naive Bayes classifiers and probabilistic networks. - Christian Borgelt; Heiko Timm; Rudolf Kruse (FUZZ-IEEE, 2000)

Data mining with graphical models. - Christian Borgelt (Ausgezeichnete Informatikdissertationen, 2000)

Advanced Fuzzy Clustering and Decision Tree Plug-Ins for Data EngineTM. - Christian Borgelt; Heiko Timm (Intelligent Systems and Soft Computing, 2000)

Problems and Prospects in Fuzzy Data Analysis. - Rudolf Kruse; Christian Borgelt; Detlef D. Nauck (Intelligent Systems and Soft Computing, 2000)

Data mining with graphical models. - Christian Borgelt (2000)

An Empirical Investigation of the K2 Metric. - Christian Borgelt; Rudolf Kruse (ECSQARU, 2001)

Learning Graphical Models With Hypertree Structure Using a Simulated Annealing Approach. - Christian Borgelt; Rudolf Kruse (FUZZ-IEEE, 2001)

Unsicherheit und Vagheit: Begriffe, Methoden, Forschungsthemen. - Christian Borgelt; Rudolf Kruse (Künstliche Intell., 2001)

Unsicherheit und Vagheit - Serviceteil. - Christian Borgelt; Rudolf Kruse (Künstliche Intell., 2001)

Graphical models - methods for data analysis and mining. - Christian Borgelt; Rudolf Kruse (Wiley, 2002)

Induction of Association Rules: Apriori Implementation. - Christian Borgelt; Rudolf Kruse (COMPSTAT, 2002)

Mining Molecular Fragments: Finding Relevant Substructures of Molecules. - Christian Borgelt; Michael R. Berthold (ICDM, 2002)

Neuro-Fuzzy-Systeme - Christian Borgelt; Frank Klawonn; Rudolf Kruse; Detlef D. Nauck (Neuro-Fuzzy-Systeme, 2003)

Unsicheres und vages Wissens. - Christian Borgelt; Heiko Timm; Rudolf Kruse (Handbuch der Künstlichen Intelligenz, 2003)

Local Structure Learning in Graphical Models. - Christian Borgelt; Rudolf Kruse (Planning Based on Decision Theory, 2003)

Speeding up fuzzy clustering with neural network techniques. - Christian Borgelt; Rudolf Kruse (FUZZ-IEEE, 2003)

On Identifying Tree-Structured Perfect Maps. - Christian Borgelt (KI, 2003)

Operations and evaluation measures for learning possibilistic graphical models. - Christian Borgelt; Rudolf Kruse (Artif. Intell., 2003)

Information mining. - Rudolf Kruse; Christian Borgelt (Int. J. Approx. Reason., 2003)

Learning possibilistic graphical models from data. - Christian Borgelt; Rudolf Kruse (IEEE Trans. Fuzzy Syst., 2003)

Recursion Pruning for the Apriori Algorithm. - Christian Borgelt (FIMI, 2004)

Information measures in fuzzy decision trees. - Xiaomeng Wang; Christian Borgelt (FUZZ-IEEE, 2004)

Learning vector quantization: cluster size and cluster number. - Christian Borgelt; Daniela Girimonte; Giuseppe Acciani (ISCAS (5), 2004)

Modeling and diagnosis of analog circuits with probabilistic graphical models. - Christian Borgelt; Daniela Girimonte; Giuseppe Acciani (ISCAS (4), 2004)

Experiments in Term Weighting and Keyword Extraction in Document Clustering. - Christian Borgelt; Andreas Nürnberger (LWA, 2004)

Shape and Size Regularization in Expectation Maximization and Fuzzy Clustering. - Christian Borgelt; Rudolf Kruse (PKDD, 2004)

Advanced pruning strategies to speed up mining closed molecular fragments. - Christian Borgelt; Thorsten Meinl; Michael R. Berthold (SMC (5), 2004)

Probabilistische grafische Modellle und ihre Anwendung in der Automobilindustrie. - Christian Borgelt; Rudolf Kruse (Datenbank-Spektrum, 2004)

An extension to possibilistic fuzzy cluster analysis. - Heiko Timm; Christian Borgelt; Christian Döring; Rudolf Kruse (Fuzzy Sets Syst., 2004)

Large scale mining of molecular fragments with wildcards. - Heiko Hofer; Christian Borgelt; Michael R. Berthold (Intell. Data Anal., 2004)

Molecular Fragment Mining for Drug Discovery. - Christian Borgelt; Michael R. Berthold; David E. Patterson (ECSQARU, 2005)

Probabilistic Graphical Models for the Diagnosis of Analog Electrical Circuits. - Christian Borgelt; Rudolf Kruse (ECSQARU, 2005)

Fuzzy Learning Vector Quantization with Size and Shape Parameters. - Christian Borgelt; Andreas Nürnberger; Rudolf Kruse (FUZZ-IEEE, 2005)

Effects of Irrelevant Attributes in Fuzzy Clustering. - Christian Döring; Christian Borgelt; Rudolf Kruse (FUZZ-IEEE, 2005)

Fuzzy frequent pattern discovering based on recursive elimination. - Xiaomeng Wang; Christian Borgelt; Rudolf Kruse (ICMLA, 2005)

Minimum Weight Triangulation by Cutting Out Triangles. - Magdalene Grantson; Christian Borgelt; Christos Levcopoulos (ISAAC, 2005)

Finding the Number of Fuzzy Clusters by Resampling. - Christian Borgelt; Rudolf Kruse (FUZZ-IEEE, 2006)

Canonical Forms for Frequent Graph Mining. - Christian Borgelt (GfKl, 2006)

Full Perfect Extension Pruning for Frequent Graph Mining. - Christian Borgelt; Thorsten Meinl (ICDM Workshops, 2006)

Prototype-less Fuzzy Clustering. - Christian Borgelt (FUZZ-IEEE, 2007)

Learning Undirected Possibilistic Networks with Conditional Independence Tests. - Christian Borgelt (FUZZ-IEEE, 2007)

FrIDA - A Free Intelligent Data Analysis Toolbox. - Christian Borgelt; Gil Gonzáles-Rodríguez (FUZZ-IEEE, 2007)

Graph Mining: Repository vs. Canonical Form. - Christian Borgelt; Mathias Fiedler (GfKl, 2007)

Subgraph Support in a Single Large Graph. - Mathias Fiedler; Christian Borgelt (ICDM Workshops, 2007)

Support Computation for Mining Frequent Subgraphs in a Single Graph. - Mathias Fiedler; Christian Borgelt (MLG, 2007)

Resampling for Fuzzy Clustering. - Christian Borgelt (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2007)

Feature weighting and feature selection in fuzzy clustering. - Christian Borgelt (FUZZ-IEEE, 2008)

Fuzzy Subspace Clustering. - Christian Borgelt (GfKl, 2008)

Fixed Parameter Algorithms for the Minimum Weight Triangulation Problem. - Magdalene G. Borgelt; Christian Borgelt; Christos Levcopoulos (Int. J. Comput. Geom. Appl., 2008)

(Approximate) Frequent Item Set Mining Made Simple with a Split and Merge Algorithm. - Christian Borgelt; Xiaomeng Wang (Scalable Fuzzy Algorithms for Data Management and Analysis, 2009)

SaM: A Split and Merge Algorithm for Fuzzy Frequent Item Set Mining. - Christian Borgelt; Xiaomeng Wang (IFSA/EUSFLAT Conf., 2009)

Identification of neurons participating in cell assemblies. - Sonja Grün; Denise Berger; Christian Borgelt (ICASSP, 2009)

Accelerating fuzzy clustering. - Christian Borgelt (Inf. Sci., 2009)

Full Perfect Extension Pruning for Frequent Subgraph Mining. - Christian Borgelt; Thorsten Meinl (Mining Complex Data, 2009)

Selecting the Links in BisoNets Generated from Document Collections. - Marc Segond; Christian Borgelt (IDA, 2010)

Efficient Identification of Assembly Neurons within Massively Parallel Spike Trains. - Denise Berger; Christian Borgelt; Sebastien Louis; Abigail Morrison; Sonja Grün (Comput. Intell. Neurosci., 2010)

A conditional independence algorithm for learning undirected graphical models. - Christian Borgelt (J. Comput. Syst. Sci., 2010)

Complexity distribution as a measure for assembly size and temporal precision. - Sebastien Louis; Christian Borgelt; Sonja Grün (Neural Networks, 2010)

Simple Algorithms for Frequent Item Set Mining. - Christian Borgelt (Advances in Machine Learning II, 2010)

Guide to Intelligent Data Analysis - How to Intelligently Make Sense of Real Data. - Michael R. Berthold; Christian Borgelt; Frank Höppner; Frank Klawonn (Springer, 2010)

Finding closed frequent item sets by intersecting transactions. - Christian Borgelt; Xiaoyuan Yang 001; Rubén Nogales-Cadenas; Pedro Carmona-Saez; Alberto D. Pascual-Montano (EDBT, 2011)

Frequent route based continuous moving object location- and density prediction on road networks. - Gyözö Gidófalvi; Manohar Kaul; Christian Borgelt; Torben Bach Pedersen (GIS, 2011)

Mining Fault-Tolerant Item Sets Using Subset Size Occurrence Distributions. - Christian Borgelt; Tobias Kötter (IDA, 2011)

Finding Ensembles of Neurons in Spike Trains by Non-linear Mapping and Statistical Testing. - Christian Braune; Christian Borgelt; Sonja Grün (IDA, 2011)

Item Set Mining Based on Cover Similarity. - Marc Segond; Christian Borgelt (PAKDD (2), 2011)

Assembly Detection in Continuous Neural Spike Train Data. - Christian Braune; Christian Borgelt; Sonja Grün (IDA, 2012)

Fuzzy Frequent Pattern Mining in Spike Trains. - David Picado-Muiño; Iván Castro León; Christian Borgelt (IDA, 2012)

Soft Pattern Mining in Neuroscience. - Christian Borgelt (SMPS, 2012)

New algorithms for finding approximate frequent item sets. - Christian Borgelt; Christian Braune; Tobias Kötter; Sonja Grün (Soft Comput., 2012)

Frequent item set mining. - Christian Borgelt (WIREs Data Mining Knowl. Discov., 2012)

Network Creation: Overview. - Christian Borgelt (Bisociative Knowledge Discovery, 2012)

Selecting the Links in BisoNets Generated from Document Collections. - Marc Segond; Christian Borgelt (Bisociative Knowledge Discovery, 2012)

Cover Similarity Based Item Set Mining. - Marc Segond; Christian Borgelt (Bisociative Knowledge Discovery, 2012)

Computational Intelligence - A Methodological Introduction. - Rudolf Kruse; Christian Borgelt; Frank Klawonn; Christian Moewes; Matthias Steinbrecher; Pascal Held (Springer, 2013)

Unsicheres und vages Wissen. - Christian Borgelt; Christian Braune; Heiko Timm; Rudolf Kruse (Handbuch der Künstlichen Intelligenz, 2013)

Prototype Construction for Clustering of Point Processes based on Imprecise Synchrony. - Christian Borgelt; Christian Braune (EUSFLAT Conf., 2013)

Incremental Frequent Route Based Trajectory Prediction. - Anja Bachmann; Christian Borgelt; Gyözö Gidófalvi (CTS@SIGSPATIAL, 2013)

Finding Frequent Patterns in Parallel Point Processes. - Christian Borgelt; David Picado-Muiño (IDA, 2013)

Behavioral Clustering for Point Processes. - Christian Braune; Christian Borgelt; Rudolf Kruse (IDA, 2013)

Statistical evaluation of synchronous spike patterns extracted by frequent item set mining. - Emiliano Torre; David Picado-Muiño; Michael Denker; Christian Borgelt; Sonja Grün (Frontiers Comput. Neurosci., 2013)

Finding neural assemblies with frequent item set mining. - David Picado-Muiño; Christian Borgelt; Denise Berger; George L. Gerstein; Sonja Grün (Frontiers Neuroinformatics, 2013)

Simple Pattern Spectrum Estimation for Fast Pattern Filtering with CoCoNAD. - Christian Borgelt; David Picado-Muiño (IDA, 2014)

Frequent item set mining for sequential data: Synchrony in neuronal spike trains. - David Picado-Muiño; Christian Borgelt (Intell. Data Anal., 2014)

Fuzzy characterization of spike synchrony in parallel spike trains. - David Picado-Muiño; Iván Castro León; Christian Borgelt (Soft Comput., 2014)

Mining Frequent Parallel Episodes with Selective Participation. - Christian Borgelt; Christian Braune; Kristian Loewe; Rudolf Kruse (IFSA-EUSFLAT, 2015)

Mining Frequent Synchronous Patterns with a Graded Notion of Synchrony. - Salatiel Ezennaya-Gomez; Christian Borgelt (IFSA-EUSFLAT, 2015)

Automatic learning of synchrony in neuronal electrode recordings. - David Picado-Muiño; Christian Borgelt (IFSA-EUSFLAT, 2015)

Mining Significant Frequent Patterns in Parallel Episodes with a Graded Notion of Synchrony and Selective Participation. - Salatiel Ezennaya-Gomez; Christian Borgelt (IJCCI (NCTA), 2015)

Handling Selective Participation in Neuron Assembly Detection. - Salatiel Ezennaya-Gomez; Christian Borgelt; Christian Braune; Kristian Loewe; Rudolf Kruse (IJCCI (Selected Papers), 2015)

Test Statistics for the Identification of Assembly Neurons in Parallel Spike Trains. - David Picado-Muiño; Christian Borgelt (Comput. Intell. Neurosci., 2015)

Bedeutung von Zugehörigkeitsgraden in der Fuzzy-Technologie. - Christian Borgelt; Rudolf Kruse (Inform. Spektrum, 2015)

Handling Noise and Outliers in Fuzzy Clustering. - Christian Borgelt; Christian Braune; Marie-Jeanne Lesot; Rudolf Kruse (Fifty Years of Fuzzy Logic and its Applications, 2015)

Agglomerative Fuzzy Clustering. - Christian Borgelt; Rudolf Kruse (SMPS, 2016)

Memory-Efficient Analysis of Dense Functional Connectomes. - Kristian Loewe; Sarah E. Donohue; Mircea Ariel Schoenfeld; Rudolf Kruse; Christian Borgelt (Frontiers Neuroinformatics, 2016)

Significant Frequent Item Sets Via Pattern Spectrum Filtering. - Christian Borgelt; David Picado-Muiño (Fuzzy Technology, 2016)

Computational Intelligence - A Methodological Introduction, Second Edition - Rudolf Kruse; Christian Borgelt; Christian Braune; Sanaz Mostaghim; Matthias Steinbrecher (Springer, 2016)

Training Neural Networks to Distinguish Craving Smokers, Non-craving Smokers, and Non-smokers. - Christoph Doell; Sarah E. Donohue; Cedrik Pätz; Christian Borgelt (IDA, 2018)

Communication-Free Widened Learning of Bayesian Network Classifiers Using Hashed Fiedler Vectors. - Oliver R. Sampson; Christian Borgelt; Michael R. Berthold (IDA, 2018)

Learned Feature Generation for Molecules. - Patrick Winter; Christian Borgelt; Michael R. Berthold (IDA, 2018)

Residual Neural Networks to Distinguish Craving Smokers, Non-craving Smokers and Non-smokers by their EEG signals. - Christoph Doell; Sarah E. Donohue; Christian Borgelt (SSCI, 2018)

Mining Frequent Synchronous Patterns based on Item Cover Similarity. - Salatiel Ezennaya-Gomez; Christian Borgelt (Int. J. Comput. Intell. Syst., 2018)

Wide and Deep Reinforcement Learning for Grid-based Action Games. - Juan M. Montoya; Christian Borgelt (ICAART (2), 2019)

Wide and Deep Reinforcement Learning Extended for Grid-Based Action Games. - Juan M. Montoya; Christoph Doell; Christian Borgelt (ICAART (Revised Selected Papers), 2019)

Widened Learning of Index Tracking Portfolios. - Iuliia Gavriushina; Oliver Sampson; Michael R. Berthold; Winfried Pohlmeier; Christian Borgelt (ICMLA, 2019)

Aggregation of Subclassifications: Methods, Tools and Experiments. - Christoph Doell; Christian Borgelt (SSCI, 2019)

Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning. - Inés Couso; Christian Borgelt; Eyke Hüllermeier; Rudolf Kruse (IEEE Comput. Intell. Mag., 2019)

AlgoNet: C∞ Smooth Algorithmic Neural Networks. - Felix Petersen; Christian Borgelt; Oliver Deussen (CoRR, 2019)

Unsicheres, impräzises und unscharfes Wissen. - Christian Borgelt; Christian Braune; Rudolf Kruse (Handbuch der Künstlichen Intelligenz, 2020)

Initializing k-means Clustering. - Christian Borgelt; Olha Yarikova (DATA, 2020)

Even Faster Exact k-Means Clustering. - Christian Borgelt (IDA, 2020)

Guide to Intelligent Data Science - How to Intelligently Make Use of Real Data, Second Edition - Michael R. Berthold; Christian Borgelt; Frank Höppner; Frank Klawonn; Rosaria Silipo (Springer, 2020)

Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision. - Felix Petersen; Christian Borgelt; Hilde Kuehne; Oliver Deussen (ICML, 2021)

Gradient Ascent for Best Response Regression. - Victoria Racher; Christian Borgelt (IDA, 2021)

Learning with Algorithmic Supervision via Continuous Relaxations. - Felix Petersen; Christian Borgelt; Hilde Kuehne; Oliver Deussen (NeurIPS, 2021)

GenDR: A Generalized Differentiable Renderer. - Felix Petersen; Bastian Goldluecke; Christian Borgelt; Oliver Deussen (CVPR, 2022)

Monotonic Differentiable Sorting Networks. - Felix Petersen; Christian Borgelt; Hilde Kuehne; Oliver Deussen (ICLR, 2022)

Differentiable Top-k Classification Learning. - Felix Petersen; Hilde Kuehne; Christian Borgelt; Oliver Deussen (ICML, 2022)

Deep Differentiable Logic Gate Networks. - Felix Petersen; Christian Borgelt; Hilde Kuehne; Oliver Deussen (NeurIPS, 2022)

Fast Multiplex Graph Association Rules for Link Prediction. - Michele Coscia; Christian Borgelt; Michael Szell (CoRR, 2022)

Computational Intelligence - A Methodological Introduction, Third Edition - Rudolf Kruse; Sanaz Mostaghim; Christian Borgelt; Christian Braune; Matthias Steinbrecher (Springer, 2022)

Trustworthy Medical Operational AI: Marrying AI and Regulatory Requirements. - Fabian Berns; Georg Zimmermann; Christian Borgelt; Niclas Heilig; Jan Kirchhoff; Florian Stumpe (IEEE Big Data, 2023)

ISAAC Newton: Input-based Approximate Curvature for Newton's Method. - Felix Petersen; Tobias Sutter; Christian Borgelt; Dongsung Huh; Hilde Kuehne; Yuekai Sun; Oliver Deussen (ICLR, 2023)

Uncertainty Quantification via Stable Distribution Propagation. - Felix Petersen; Aashwin Ananda Mishra; Hilde Kuehne; Christian Borgelt; Oliver Deussen; Mikhail Yurochkin (ICLR, 2024)

TrAct: Making First-layer Pre-Activations Trainable. - Felix Petersen; Christian Borgelt; Stefano Ermon (NeurIPS, 2024)

Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms. - Felix Petersen; Christian Borgelt; Tobias Sutter; Hilde Kuehne; Oliver Deussen; Stefano Ermon (NeurIPS, 2024)

Convolutional Differentiable Logic Gate Networks. - Felix Petersen; Hilde Kuehne; Christian Borgelt; Julian Welzel; Stefano Ermon (NeurIPS, 2024)

Generalizing Stochastic Smoothing for Differentiation and Gradient Estimation. - Felix Petersen; Christian Borgelt; Aashwin Ananda Mishra; Stefano Ermon (CoRR, 2024)

Variable-Size Genetic Network Programming for Portfolio Optimization with Trading Rules. - Fabian Köhnke; Christian Borgelt (EvoApplications (2), 2025)

Data Augmentation of Time-Series Data in Human Movement Biomechanics: A Scoping Review. - Christina Halmich; Lucas Höschler; Christoph Schranz; Christian Borgelt (CoRR, 2025)