Approximation of continuous functions by RBF and KBF networks. - Vera Kurková; Katerina Hlavácková (ESANN, 1994)

An optimized RBF network for approximation of functions. - Michel Verleysen; Katerina Hlavácková (ESANN, 1994)

An upper estimate of the error of approximation of continuous multivariable functions by KBF networks. - Katerina Hlavácková (ESANN, 1995)

Rates of approximation of real-valued boolean functions by neural networks. - Katerina Hlavácková; Vera Kurková (ESANN, 1996)

Upper Bounds on the Approximation Rates of Real-valued Boolean Functions by Neural Networks. - Katerina Hlavácková; Vera Kurková; Petr Savický (ICANNGA, 1997)

Placing spline knots in neural networks using splines as activation functions. - Katerina Hlavácková; Michel Verleysen (Neurocomputing, 1997)

Algorithm of Incremental Approximation Using Variation of a Function with Respect to a Subset. - Katerina Hlavácková; Marcello Sanguineti (NC, 1998)

Representations and rates of approximation of real-valued Boolean functions by neural networks. - Vera Kurková; Petr Savický; Katerina Hlavácková (Neural Networks, 1998)

Some Comparisons Between Linear Approximation and Approximation by Neural Networks. - Marcello Sanguineti; Katerina Hlavácková-Schindler (ICANNGA, 1999)

An Incremental Algorithm for Parallel Training of the Size and the Weights in a Feedforward Neural Network. - Katerina Hlavácková-Schindler; Manfred M. Fischer (Neural Process. Lett., 2000)

Fitting of a closed planar curve representing a profile of an archaeological fragment. - Katerina Hlavácková-Schindler; Martin Kampel; Robert Sablatnig (Virtual Reality, Archeology, and Cultural Heritage, 2001)

Computational Intelligence approaches to causality detection. - Katerina Hlavácková-Schindler; Pablo F. Verdes (ESANN, 2007)

Mutual Information Estimation in Higher Dimensions: A Speed-Up of a k -Nearest Neighbor Based Estimator. - Martin Vejmelka; Katerina Hlavácková-Schindler (ICANNGA (1), 2007)

Tikhonov Regularization Parameter in Reproducing Kernel Hilbert Spaces with Respect to the Sensitivity of the Solution. - Katerina Hlavácková-Schindler (ICANN (1), 2008)

Graphical Lasso Granger Method with 2-Levels-Thresholding for Recovering Causality Networks. - Sergiy Pereverzyev Jr.; Katerina Hlavácková-Schindler (System Modelling and Optimization, 2013)

Lasso Granger Causal Models: Some Strategies and Their Efficiency for Gene Expression Regulatory Networks. - Katerina Hlavácková-Schindler; Sergiy Pereverzyev Jr. (Decision Making, 2015)

Dependency Anomaly Detection for Heterogeneous Time Series: A Granger-Lasso Approach. - Sahar Behzadi; Katerina Hlavácková-Schindler; Claudia Plant (ICDM Workshops, 2017)

Granger Causality for Heterogeneous Processes. - Sahar Behzadi; Katerina Hlavácková-Schindler; Claudia Plant (PAKDD (3), 2019)

Graphical Granger Causality by Information-Theoretic Criteria. - Katerina Hlavácková-Schindler; Claudia Plant (ECAI, 2020)

Poisson Graphical Granger Causality by Minimum Message Length. - Katerina Hlavácková-Schindler; Claudia Plant (ECML/PKDD (1), 2020)

The Data Mining Group at University of Vienna. - Muzaffer Can Altinigneli; Lena Greta Marie Bauer; Sahar Behzadi; Robert Fritze; Katerina Hlavácková-Schindler; Maximilian Leodolter; Lukas Miklautz; Martin Perdacher; Ylli Sadikaj; Benjamin Schelling; Claudia Plant (Datenbank-Spektrum, 2020)

Heterogeneous Graphical Granger Causality by Minimum Message Length. - Katerina Hlavácková-Schindler; Claudia Plant (Entropy, 2020)

Causal Discovery in Hawkes Processes by Minimum Description Length. - Amirkasra Jalaldoust; Katerina Hlavácková-Schindler; Claudia Plant (AAAI, 2022)

AWT - Clustering Meteorological Time Series Using an Aggregated Wavelet Tree. - Christina Pacher; Irene Schicker; Rosmarie deWit; Katerina Hlavácková-Schindler; Claudia Plant (DSAA, 2022)

Interpretable Gait Recognition by Granger Causality. - Michal Balazia; Katerina Hlavácková-Schindler; Petr Sojka; Claudia Plant (ICPR, 2022)

Causal Inference for Heterogeneous Data and Information Theory. - Katerina Hlavácková-Schindler (Entropy, 2023)

Advancing Anomaly Detection: Non-Semantic Financial Data Encoding with LLMs. - Alexander Bakumenko; Katerina Hlavácková-Schindler; Claudia Plant; Nina C. Hubig (CoRR, 2024)

Granger Causal Inference in Multivariate Hawkes Processes by Minimum Message Length. - Katerina Hlavácková-Schindler; Anna Melnykova; Irene Tubikanec (J. Mach. Learn. Res., 2024)

Advancing Anomaly Detection: Non-Semantic Financial Data Encoding With Large Language Models. - Alexander Bakumenko; Katerina Hlavácková-Schindler; Claudia Plant; Nina C. Hubig (IEEE Access, 2025)

Minimum Description Length and Multi-Criteria Decision Analysis in Predictive Modeling. - Petr Silhavy; Katerina Hlavácková-Schindler; Radek Silhavy (IEEE Access, 2025)

Motif Discovery Framework for Psychiatric EEG Data Classification. - Melanija Kraljevska; Katerina Hlavácková-Schindler; Lukas Miklautz; Claudia Plant (CoRR, 2025)

Cause or Trigger? From Philosophy to Causal Modeling. - Katerina Hlavácková-Schindler; Rainer Wöß; Vera Pecorino; Philip Schindler (CoRR, 2025)