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Katerina Hlavácková-Schindler
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2020 – today
- 2024
- [j7]Katerina Hlavácková-Schindler, Anna Melnykova, Irene Tubikanec:
Granger Causal Inference in Multivariate Hawkes Processes by Minimum Message Length. J. Mach. Learn. Res. 25: 133:1-133:26 (2024) - [i5]Alexander Bakumenko, Katerina Hlavácková-Schindler, Claudia Plant, Nina C. Hubig:
Advancing Anomaly Detection: Non-Semantic Financial Data Encoding with LLMs. CoRR abs/2406.03614 (2024) - 2023
- [j6]Katerina Hlavácková-Schindler
:
Causal Inference for Heterogeneous Data and Information Theory. Entropy 25(6): 910 (2023) - [i4]Katerina Hlavácková-Schindler, Anna Melnykova
Granger Causal Inference in Multivariate Hawkes Processes by Minimum Message Length. CoRR abs/2309.02027 (2023) - 2022
- [c19]Amirkasra Jalaldoust, Katerina Hlavácková-Schindler, Claudia Plant:
Causal Discovery in Hawkes Processes by Minimum Description Length. AAAI 2022: 6978-6987 - [c18]Christina Pacher, Irene Schicker, Rosmarie deWit, Katerina Hlavácková-Schindler
AWT - Clustering Meteorological Time Series Using an Aggregated Wavelet Tree. DSAA 2022: 1-10 - [c17]Michal Balazia, Katerina Hlavácková-Schindler
Interpretable Gait Recognition by Granger Causality. ICPR 2022: 1069-1075 - [i3]Amirkasra Jalaldoust, Katerina Hlavácková-Schindler
Causal Discovery in Hawkes Processes by Minimum Description Length. CoRR abs/2206.06124 (2022) - [i2]Michal Balazia, Katerina Hlavácková-Schindler
Interpretable Gait Recognition by Granger Causality. CoRR abs/2206.06714 (2022) - [i1]Christina Pacher, Irene Schicker, Rosmarie deWit, Katerina Hlavácková-Schindler
AWT - Clustering Meteorological Time Series Using an Aggregated Wavelet Tree. CoRR abs/2212.06642 (2022) - 2020
- [j5]Muzaffer Can Altinigneli, Lena Greta Marie Bauer, Sahar Behzadi, Robert Fritze
The Data Mining Group at University of Vienna. Datenbank-Spektrum 20(1): 71-79 (2020) - [j4]Katerina Hlavácková-Schindler
Heterogeneous Graphical Granger Causality by Minimum Message Length. Entropy 22(12): 1400 (2020) - [c16]Katerina Hlavácková-Schindler
Graphical Granger Causality by Information-Theoretic Criteria. ECAI 2020: 1459-1466 - [c15]Katerina Hlavácková-Schindler
Poisson Graphical Granger Causality by Minimum Message Length. ECML/PKDD (1) 2020: 526-541
2010 – 2019
- 2019
- [c14]Sahar Behzadi, Katerina Hlavácková-Schindler
Granger Causality for Heterogeneous Processes. PAKDD (3) 2019: 463-475 - 2017
- [c13]Sahar Behzadi, Katerina Hlavácková-Schindler
Dependency Anomaly Detection for Heterogeneous Time Series: A Granger-Lasso Approach. ICDM Workshops 2017: 1090-1099 - 2015
- [p1]Katerina Hlavácková-Schindler
Lasso Granger Causal Models: Some Strategies and Their Efficiency for Gene Expression Regulatory Networks. Decision Making 2015: 91-117 - 2013
- [c12]Sergiy Pereverzyev Jr., Katerina Hlavácková-Schindler:
Graphical Lasso Granger Method with 2-Levels-Thresholding for Recovering Causality Networks. System Modelling and Optimization 2013: 220-229
2000 – 2009
- 2008
- [c11]Katerina Hlavácková-Schindler
Tikhonov Regularization Parameter in Reproducing Kernel Hilbert Spaces with Respect to the Sensitivity of the Solution. ICANN (1) 2008: 215-224 - 2007
- [c10]Katerina Hlavácková-Schindler, Pablo F. Verdes:
Computational Intelligence approaches to causality detection. ESANN 2007: 433-440 - [c9]Martin Vejmelka, Katerina Hlavácková-Schindler
Mutual Information Estimation in Higher Dimensions: A Speed-Up of a k -Nearest Neighbor Based Estimator. ICANNGA (1) 2007: 790-797 - 2001
- [c8]Katerina Hlavácková-Schindler, Martin Kampel
Fitting of a closed planar curve representing a profile of an archaeological fragment. Virtual Reality, Archeology, and Cultural Heritage 2001: 263-270 - 2000
- [j3]Katerina Hlavácková-Schindler
An Incremental Algorithm for Parallel Training of the Size and the Weights in a Feedforward Neural Network. Neural Process. Lett. 11(2): 131-138 (2000)
1990 – 1999
- 1999
- [c7]Marcello Sanguineti, Katerina Hlavácková-Schindler
Some Comparisons Between Linear Approximation and Approximation by Neural Networks. ICANNGA 1999: 172-177 - 1998
- [j2]Vera Kurková
Representations and rates of approximation of real-valued Boolean functions by neural networks. Neural Networks 11(4): 651-659 (1998) - [c6]Katerina Hlavácková, Marcello Sanguineti:
Algorithm of Incremental Approximation Using Variation of a Function with Respect to a Subset. NC 1998: 896-899 - 1997
- [j1]Katerina Hlavácková
Placing spline knots in neural networks using splines as activation functions. Neurocomputing 17(3-4): 159-166 (1997) - [c5]Katerina Hlavácková, Vera Kurková, Petr Savický:
Upper Bounds on the Approximation Rates of Real-valued Boolean Functions by Neural Networks. ICANNGA 1997: 495-499 - 1996
- [c4]Katerina Hlavácková, Vera Kurková:
Rates of approximation of real-valued boolean functions by neural networks. ESANN 1996 - 1995
- [c3]Katerina Hlavácková:
An upper estimate of the error of approximation of continuous multivariable functions by KBF networks. ESANN 1995 - 1994
- [c2]Vera Kurková, Katerina Hlavácková:
Approximation of continuous functions by RBF and KBF networks. ESANN 1994 - [c1]Michel Verleysen, Katerina Hlavácková:
An optimized RBF network for approximation of functions. ESANN 1994
Coauthor Index
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