Alfred Ultsch

发表

An algorithm for fast and reliable ESOM learning

Mario Nöcker, Fabian Mörchen, Alfred Ultsch, 2006, ESANN.

Data Mining and Knowledge Discovery with Emergent Self-Organizing Feature Maps for Multivariate Time Series

Alfred Ultsch, A. Ultsch, 1999 .

Wissensverarbeitung in neuronaler Architektur

Günther Palm, Ulrich Rückert, Alfred Ultsch, 1991, Wissensbasierte Systeme.

Explaining Ant-Based Clustering on the basis of Self-Organizing Maps

Alfred Ultsch, Lutz Herrmann, A. Ultsch, 2008, ESANN.

Visualisation and Classification with Artificial Life

Alfred Ultsch, 2000 .

11.Einsatzmöglichkeiten von Neuronalen Netzen im Umweltbereich

Alfred Ultsch, 1995 .

The Integration of Neural Networks with Symbolic Knowledge Processing

Alfred Ultsch, 1994 .

A Comparison of Algorithms to Find Differentially Expressed Genes in Microarray Data

Alfred Ultsch, Christian Pallasch, Eckhard Bergmann, 2008, GfKl.

Databionic Visualization of Music Collections According to Perceptual Distance

Mario Nöcker, Fabian Mörchen, Alfred Ultsch, 2005, ISMIR.

A connectionist knowledge-acquisition tool: CONKAT

Alfred Ultsch, R. Mantyk, G. Halmans, 1993 .

Are there Cluster of Communities with the Same Dynamic Behaviour

Alfred Ultsch, Martin Behnisch, 2010 .

Control for knowledge based information retrieval

Alfred Ultsch, 1987 .

Clustering Temporal Population Patterns in Switzerland (1850-2000)

Alfred Ultsch, Martin Behnisch, 2010, GfKl.

Data normalization with self-organizing feature maps

Alfred Ultsch, Gunter Halmans, 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

Identification of Molecular Fingerprints in Human Heat Pain Thresholds by Use of an Interactive Mixture Model R Toolbox (AdaptGauss)

Jörn Lötsch, Alfred Ultsch, Michael C. Thrun, 2015, International journal of molecular sciences.

Neural networks and their rules for classification in marine geology

Alfred Ultsch, Dieter Korus, Achim Wehrmann, 2007 .

Urban Data Mining Using Emergent SOM

Alfred Ultsch, Martin Behnisch, 2007, GfKl.

Knowledge Extraction from Self-Organizing Neural Networks

Alfred Ultsch, A. Ultsch, 1993 .

Knowledge Extraction from Artificial Neural Networks and Applications

Alfred Ultsch, Heng Li, Gabriela Guimarães, 1993, Transputer-Anwender-Treffen.

Is Log Ratio a Good Value for Measuring Return in Stock Investments?

Alfred Ultsch, 2008, GfKl.

Neuronale Netze zur Unterstützung der Umweltforschung

Alfred Ultsch, Günter Halmans, H. Peter Siemon, 1991, Informatik für den Umweltschutz.

Self Organizing Neural Networks perform different from statistical k-means clustering

Alfred Ultsch, A. Ultsch, 2003 .

Clustering with Swarm Algorithms Compared to Emergent SOM

Alfred Ultsch, Lutz Herrmann, A. Ultsch, 2009, WSOM.

Learning of control knowledge for symbolic proofs with backpropagation networks

Alfred Ultsch, Ulrich Hartmann, Volker Weber, 1990 .

Visual mining in music collections with Emergent SOM

Sebastian Risi, Alfred Ultsch, Pascal Lehwark, 2007 .

U*F clustering: a new performant "cluster-mining" method based on segmentation of Self-Organizing Maps

Fabien Moutarde, Alfred Ultsch, F. Moutarde, 2005 .

Automatic Acquisition of Medical Knowledge from Data sets with Neural Networks

Alfred Ultsch, Heng Li, Stefan Farsch, 1995 .

Knowledge discovery in DNA microarray data of cancer patients with emergent self organizing maps

Alfred Ultsch, David Kämpf, 2004, ESANN.

Discovering Temporal Knowledge in Multivariate Time Series

Fabian Mörchen, Alfred Ultsch, 2004, GfKl.

The Architecture of Ant-Based Clustering to Improve Topographic Mapping

Alfred Ultsch, Lutz Herrmann, A. Ultsch, 2008, ANTS Conference.

Strengths and Weaknesses of Ant Colony Clustering

Alfred Ultsch, Lutz Herrmann, A. Ultsch, 2008, GfKl.

Selbstorganisierende Neuronale Netze auf Transputern

Heng Li, Alfred Ultsch, Gabriela Guimarães, 1992, Transputer-Anwender-Treffen.

KOFIS: Ein Expertensystem zur integrierten Dokumenten- und Wissensverwaltung

Hans-Jürgen Appelrath, Martin Ester, Alfred Ultsch, 1987, Expertensysteme.

An Overview of Artificial Life Approaches for Clustering

Alfred Ultsch, David Kämpf, A. Ultsch, 2005, GfKl.

A Hybrid Expert System for Avalanche Forecasting

Alfred Ultsch, Jürg Schweizer, M. Schweizer, 1994, ENTER.

Optimizing time series discretization for knowledge discovery

Fabian Mörchen, Alfred Ultsch, F. Mörchen, 2005, KDD '05.

Comparison of substructural epitopes in enzyme active sites using self-organizing maps

Gerhard Klebe, Alfred Ultsch, Katrin Kupas, 2004, J. Comput. Aided Mol. Des..

Machine-learned cluster identification in high-dimensional data

Jörn Lötsch, Alfred Ultsch, A. Ultsch, 2017, J. Biomed. Informatics.

Die Transformation experimenteller Verteilungen durch eine Self-Organizing Feature Map

Alfred Ultsch, Günter Halmans, Kira Schulz, 1991, DAGM-Symposium.

Modeling timbre distance with temporal statistics from polyphonic music

Fabian Mörchen, Alfred Ultsch, Michael Thies, 2006, IEEE Transactions on Audio, Speech, and Language Processing.

The Completion of Missing Values by Neural Nets for Data Mining

Alfred Ultsch, S. Rolf, 2002 .

Efficient mining of all margin-closed itemsets with applications in temporal knowledge discovery and classification by compression

Fabian Mörchen, Alfred Ultsch, Michael Thies, 2010, Knowledge and Information Systems.

Automatic Acquisition of Symbolic Knowledge from Subsymbolic Neural Networks

Alfred Ultsch, Dieter Korus, 1993 .

Knowledge Discovery in Spatial Planning Data: A Concept for Cluster Understanding

Alfred Ultsch, Martin Behnisch, A. Ultsch, 2015 .

U*C: Self-organized Clustering with Emergent Feature Maps

Alfred Ultsch, 2005, LWA.

Self Organized Swarms for cluster preserving Projections of high-dimensional Data

Alfred Ultsch, Lutz Herrmann, A. Ultsch, 2010, Electron. Commun. Eur. Assoc. Softw. Sci. Technol..

Finding Persisting States for Knowledge Discovery in Time Series

Fabian Mörchen, Alfred Ultsch, 2005, GfKl.

The integration of connectionist models with knowledge-based systems: hybrid systems

Alfred Ultsch, 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

U*C: Distance and Density Clustering based on Grid Projections

Alfred Ultsch, 2007, LWA.

Efficient mining of understandable patterns from multivariate interval time series

Fabian Mörchen, Alfred Ultsch, F. Mörchen, 2007, Data Mining and Knowledge Discovery.

Algorithms from and for Nature and Life - Classification and Data Analysis

Alfred Ultsch, Berthold Lausen, Dirk Van den Poel, 2013, Studies in Classification, Data Analysis, and Knowledge Organization.

Data Mining in Protein Binding Cavities

Alfred Ultsch, Katrin Kupas, A. Ultsch, 2004, GfKl.

CONKAT: a connectionist knowledge acquisition tool

Alfred Ultsch, R. Mantyk, Gunter Halmans, 1991, Proceedings of the Twenty-Fourth Annual Hawaii International Conference on System Sciences.

An Algorithm for Finding Similarities in protein Active sites

Gerhard Klebe, Alfred Ultsch, Katrin Kupas, 2005, Advances in Bioinformatics and Its Applications.

The architecture of emergent self-organizing maps to reduce projection errors

Alfred Ultsch, Lutz Herrmann, A. Ultsch, 2005, ESANN.

ESOM Visualizations for Quality Assessment in Clustering

Jörn Lötsch, Alfred Ultsch, Martin Behnisch, 2016, WSOM.

A method for automated temporal knowledge acquisition applied to sleep-related breathing disorders

Thomas Penzel, Alfred Ultsch, Gabriela Guimarães, 2001, Artif. Intell. Medicine.

Kohonen Networks on Transputers: Implementation and Animation

Alfred Ultsch, H. P. Siemon, A. Ultsch, 1990 .

Improving the Identification of Differentially Expressed Genes in cDNA Microarray Experiments

Alfred Ultsch, A. Ultsch, 2004, GfKl.

Self-Organizing-Feature-Maps versus Statistical Clustering Methods: A Benchmark

Alfred Ultsch, Claus Vetter, A. Ultsch, 1994 .

Evaluation of Automatic and Manual Knowledge Acquisition for Cerebrospinal Fluid (CSF) Diagnosis

Alfred Ultsch, Gabriela Guimarães, J. Simon, 1997, AIME.

Integration of Neural Networks and Knowledge-Based Systems in Medicine

Alfred Ultsch, Dieter Korus, T. O. Kleine, 1995, AIME.

Self Organizing Feature Maps for Logical Unification

Alfred Ultsch, Volker Weber, Gabriela Guimarães, 1994 .

A Method for Temporal Knowledge Conversion

Alfred Ultsch, Gabriela Guimarães, 1999, IDA.

Clustering with DataBots Alfred

Alfred Ultsch, 2003 .

UnitExpressions: A Rational Normalization Scheme for DNA Microarray Data

Alfred Ultsch, A. Ultsch, 2005, GfKl.

OPTIMIZING LOGICAL PROOFS WITH CONNECTIONIST NETWORKS

Alfred Ultsch, M. Mandischer, R.Hannuschka, 2006 .

Self Organized Feature Maps for Monitoring and Knowledge Aquisition of a Chemical Process

Alfred Ultsch, A. Ultsch, 1993 .

Density Estimation and Visualization for Data Containing Clusters of Unknown Structure

Alfred Ultsch, 2004, GfKl.

Self-organizing feature maps predicting sea levels

Alfred Ultsch, Frank Röske, A. Ultsch, 2002, Inf. Sci..

A machine-learned knowledge discovery method for associating complex phenotypes with complex genotypes. Application to pain

Jörn Lötsch, Alfred Ultsch, A. Ultsch, 2013, J. Biomed. Informatics.

Advances in Data Analysis, Data Handling and Business Intelligence: Proceedings of the 32nd Annual Conference of the Gesellschaft fr Klassifikation e.V., ... Data Analysis, and Knowledge Organization)

Andreas Fink, Alfred Ultsch, Berthold Lausen, 2009 .

The Precise and Efficient Identification of Medical Order Forms Using Shape Trees

Uwe Petersohn, Alfred Ultsch, Uwe Henker, 2008, GfKl.

Knowledge based retrieval in an office

Alfred Ultsch, Hans-Jürgen Appelrath, M. Ester, 1986 .

Visualization and Clustering of Tagged Music Data

Sebastian Risi, Alfred Ultsch, Pascal Lehwark, 2007, GfKl.

Understandable models Of music collections based on exhaustive feature generation with temporal statistics

Ingo Mierswa, Fabian Mörchen, Alfred Ultsch, 2006, KDD '06.

Urban data-mining: spatiotemporal exploration of multidimensional data

Alfred Ultsch, Martin Behnisch, 2009 .

Data Mining as an Application for Artificial Life

Alfred Ultsch, 2004 .

Discovering Interpretable Muscle Activation Patterns with the Temporal Data Mining Method

Fabian Mörchen, Alfred Ultsch, Olaf Hoos, 2004, PKDD.

Credible visualizations for planar projections

Alfred Ultsch, Michael C. Thrun, A. Ultsch, 2017, 2017 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM).

Visual Mining in Music Collections

Mario Nöcker, Fabian Mörchen, Alfred Ultsch, 2005, GfKl.

Extracting interpretable muscle activation patterns with time series knowledge mining

Fabian Mörchen, Alfred Ultsch, Olaf Hoos, 2005, Int. J. Knowl. Based Intell. Eng. Syst..

Fundamentale Aktienanalyse mit selbstorganisierenden datamining Methoden

Alfred Ultsch, 2001 .

Self-organizing neural networks for knowledge acquisition

Alfred Ultsch, 1992 .

Integration of neural networks with knowledge-based systems

Alfred Ultsch, Dieter Korus, 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

Label Propagation for Semi-Supervised Learning in Self-Organizing Maps

Alfred Ultsch, Lutz Herrmann, A. Ultsch, 2007 .

Knowledge Acquisition with Self-Organizing Neural Networks

Alfred Ultsch, 1992, ECAI.

An Artificial Life Approach for Semi-supervised Learning

Alfred Ultsch, Lutz Herrmann, A. Ultsch, 2007, GfKl.

Examination of Several Results of Different Cluster Analyses with a Separate View to Balancing the Economic and Ecological Performance Potential of Towns and Cities

Nguyen-Xuan Thinh, Alfred Ultsch, Martin Behnisch, 2006, GfKl.

Estimating the Number of Buildings in Germany

Alfred Ultsch, Martin Behnisch, A. Ultsch, 2008, GfKl.

Finding Music Fads by Clustering Online Radio Data with Emergent Self Organizing Maps

Alfred Ultsch, Florian Meyer, 2008, GfKl.

Mining Hierarchical Temporal Patterns in Multivariate Time Series

Fabian Mörchen, Alfred Ultsch, F. Mörchen, 2004, KI.

A neural network learning relative distances

Alfred Ultsch, A. Ultsch, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Exploiting the Structures of the U-Matrix

Jörn Lötsch, Alfred Ultsch, A. Ultsch, 2014, WSOM.

Data for: Clustering Benchmark Datasets Exploiting the Fundamental Clustering Problems

Alfred Ultsch, Michael C. Thrun, 2021 .

Explainable AI Framework for Multivariate Hydrochemical Time Series

Alfred Ultsch, Lutz Breuer, Michael C. Thrun, 2021, Mach. Learn. Knowl. Extr..

An Explainable AI System for the Diagnosis of High Dimensional Biomedical Data pdf

Alfred Ultsch, Michael C. Thrun, Jörg Hoffmann, 2021, ArXiv.

Conventional displays of structures in data compared with interactive projection-based clustering (IPBC)

Alfred Ultsch, Michael C. Thrun, Felix Pape, 2021, International Journal of Data Science and Analytics.

Correction to: Conventional displays of structures in data compared with interactive projection-based clustering (IPBC)

Alfred Ultsch, Michael C. Thrun, Felix Pape, 2021, Int. J. Data Sci. Anal..

Process Pharmacology: A Pharmacological Data Science Approach to Drug Development and Therapy

Jörn Lötsch, Alfred Ultsch, A. Ultsch, 2016, CPT: pharmacometrics & systems pharmacology.

Emergent self-organising feature maps used for prediction and prevention of churn in mobile phone markets

Alfred Ultsch, 2002 .

Picking Stocks with Emergent Self-organizing Value maps

Alfred Ultsch, Guido Deboeck, 2006 .

A data science approach to candidate gene selection of pain regarded as a process of learning and neural plasticity

Jörn Lötsch, Alfred Ultsch, Dario Kringel, 2016, Pain.

Proof of Pareto’s 80/20 Law and Precise Limits for ABC-Analysis

Alfred Ultsch, 2002 .

Emergence in Self Organizing Feature Maps

Alfred Ultsch, A. Ultsch, 2007 .

Pareto Density Estimation: A Density Estimation for Knowledge Discovery

Alfred Ultsch, A. Ultsch, 2005 .

Machine-learning-derived classifier predicts absence of persistent pain after breast cancer surgery with high accuracy

Jörn Lötsch, Alfred Ultsch, Dario Kringel, 2018, Breast cancer research and treatment.

Large scale analysis of protein‐binding cavities using self‐organizing maps and wavelet‐based surface patches to describe functional properties, selectivity discrimination, and putative cross‐reactivity

Gerhard Klebe, Alfred Ultsch, G. Klebe, 2007, Proteins.

U *-Matrix : a Tool to visualize Clusters in high dimensional Data

Alfred Ultsch, A. Ultsch, 2004 .

Pareto Density Estimation: Probability Density Estimation for Knowledge Discovery

Alfred Ultsch, A. Ultsch, 2003 .

Integrated Computational Analysis of Genes Associated with Human Hereditary Insensitivity to Pain. A Drug Repurposing Perspective

Jörn Lötsch, Alfred Ultsch, Catharina Lippmann, 2017, Front. Mol. Neurosci..

A machine-learned computational functional genomics-based approach to drug classification

Jörn Lötsch, Alfred Ultsch, A. Ultsch, 2016, European Journal of Clinical Pharmacology.

Pattern of neuropathic pain induced by topical capsaicin application in healthy subjects

Jörn Lötsch, Alfred Ultsch, Gerd Geisslinger, 2015, Pain.

Functional genomics of pain in analgesic drug development and therapy.

Jörn Lötsch, Alfred Ultsch, Gerd Geisslinger, 2013, Pharmacology & therapeutics.