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  1. 1.
    0568306 - ÚI 2024 RIV CH eng J - Journal Article
    Korel, L. - Yorsh, U. - Behr, A. S. - Kockmann, N. - Holeňa, Martin
    Text-to-Ontology Mapping via Natural Language Processing with Application to Search for Relevant Ontologies in Catalysis.
    Computers. Roč. 12, č. 1 (2023), č. článku 14. ISSN 2073-431X
    Institutional support: RVO:67985807
    Keywords : text representation learning * text classification * text preprocessing * text data * ontology
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    Method of publishing: Open access
    https://dx.doi.org/10.3390/computers12010014
    Permanent Link: https://hdl.handle.net/11104/0339633

               
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    0568306-afinoa.pdf21.9 MBOA CC BY 4.0Publisher’s postprintopen-access
     
     
  2. 2.
    0567441 - ÚI 2023 RIV CH eng J - Journal Article
    Dropka, N. - Tang, X. - Chappa, G. K. - Holeňa, Martin
    Smart Design of Cz-Ge Crystal Growth Furnace and Process.
    Crystals. Roč. 12, č. 12 (2022), č. článku 1764. ISSN 2073-4352. E-ISSN 2073-4352
    Institutional support: RVO:67985807
    Keywords : Czochralski Ge growth * CFD training data * furnace design * process design * regression tree * correlation coefficient
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    Impact factor: 2.670, year: 2021
    Method of publishing: Open access
    https://dx.doi.org/10.3390/cryst12121764
    Permanent Link: https://hdl.handle.net/11104/0338696

               
     
     
  3. 3.
    0561617 - ÚI 2023 GB J - Journal Article
    Sheikhi, A. - Mesiar, R. - Holeňa, Martin
    A dimension reduction in neural network using copula matrix.
    International Journal of General Systems. Online AUG 2022 (2023). ISSN 0308-1079. E-ISSN 1563-5104
    Institutional support: RVO:67985807
    Keywords : Principal component * copula * neural network * correlation * association measure
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    Impact factor: 2.435, year: 2021
    Method of publishing: Limited access
    https://dx.doi.org/10.1080/03081079.2022.2108029
    Permanent Link: https://hdl.handle.net/11104/0334185

               
     
     
  4. 4.
    0547633 - ÚI 2022 RIV CH eng J - Journal Article
    Dropka, N. - Böttcher, K. - Holeňa, Martin
    Development and Optimization of VGF-GaAs Crystal Growth Process Using Data Mining and Machine Learning Techniques.
    Crystals. Roč. 11, č. 10 (2021), č. článku 1218. ISSN 2073-4352. E-ISSN 2073-4352
    R&D Projects: GA ČR(CZ) GA18-18080S
    Institutional support: RVO:67985807
    Keywords : VGF-GaAs growth * machine learning * data mining * decision trees * correlation analysis * PCA biplot * k-means clustering
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    Impact factor: 2.670, year: 2021
    Method of publishing: Open access
    http://dx.doi.org/10.3390/cryst11101218
    Permanent Link: http://hdl.handle.net/11104/0323829

               
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    0547633-afin.pdf33.2 MBOA CC BY 4.0Publisher’s postprintopen-access
     
     
  5. 5.
    0541776 - ÚI 2022 RIV CH eng J - Journal Article
    Dropka, N. - Ecklebe, S. - Holeňa, Martin
    Real Time Predictions of VGF-GaAs Growth Dynamics by LSTM Neural Networks.
    Crystals. Roč. 11, č. 2 (2021), č. článku 138. ISSN 2073-4352. E-ISSN 2073-4352
    R&D Projects: GA ČR(CZ) GA18-18080S
    Institutional support: RVO:67985807
    Keywords : neural networks * crystal growth * GaAs * process control * digital twins
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    Impact factor: 2.670, year: 2021
    Method of publishing: Open access
    Permanent Link: http://hdl.handle.net/11104/0319303

               
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    541776-aoa.pdf23.5 MBOA CC BY 4.0Publisher’s postprintopen-access
     
     
  6. 6.
    0525271 - ÚI 2021 RIV US eng J - Journal Article
    Górecki, J. - Hofert, M. - Holeňa, Martin
    Hierarchical Archimedean Copulas for Matlab and Octave: The HACopula Toolbox.
    Journal of Statistical Software. Roč. 93, č. 10 (2020), s. 1-36. ISSN 1548-7660. E-ISSN 1548-7660
    R&D Projects: GA ČR GA17-01251S
    Institutional support: RVO:67985807
    Keywords : copula * hierarchical Archimedean copula * structure * family * estimation * collapsing * sampling * goodness-of-fit * Kendall’s tau * tail dependence * MATLAB * Octave
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    Impact factor: 6.440, year: 2020
    Method of publishing: Open access
    Permanent Link: http://hdl.handle.net/11104/0309452

               
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    0525271-aoa.pdf62.5 MBOA CC BY 3.0Publisher’s postprintopen-access
     
     
  7. 7.
    0522404 - ÚI 2021 RIV GB eng J - Journal Article
    Kopp, M. - Pevný, T. - Holeňa, Martin
    Anomaly explanation with random forests.
    Expert Systems With Applications. Roč. 149, 1 July (2020), č. článku 113187. ISSN 0957-4174. E-ISSN 1873-6793
    R&D Projects: GA ČR GA17-01251S
    Grant - others: GA ČR(CZ) GA18-21409S
    Program: GA
    Institutional support: RVO:67985807
    Keywords : Anomaly detection * Anomaly explanation * Classification rules * Feature selection * Random forests
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    Impact factor: 6.954, year: 2020
    Method of publishing: Limited access
    http://dx.doi.org/10.1016/j.eswa.2020.113187
    Permanent Link: http://hdl.handle.net/11104/0306903

               
     
     
  8. 8.
    0505764 - ÚI 2020 RIV NL eng J - Journal Article
    Dropka, N. - Holeňa, Martin - Ecklebe, S. - Frank-Rotsch, C. - Winkler, J.
    Fast Forecasting of VGF Crystal Growth Process by Dynamic Neural Networks.
    Journal of Crystal Growth. Roč. 521, 1 September (2019), s. 9-14. ISSN 0022-0248. E-ISSN 1873-5002
    R&D Projects: GA ČR(CZ) GA18-18080S
    Institutional support: RVO:67985807
    Keywords : Computer simulation * Fluid flows * Gradient freeze technique
    OECD category: Condensed matter physics (including formerly solid state physics, supercond.)
    Impact factor: 1.632, year: 2019
    Method of publishing: Limited access
    http://dx.doi.org/10.1016/j.jcrysgro.2019.05.022
    Permanent Link: http://hdl.handle.net/11104/0297153

               
     
     
  9. 9.
    0498868 - ÚI 2020 RIV US eng J - Journal Article
    Bajer, L. - Pitra, Z. - Repický, J. - Holeňa, Martin
    Gaussian Process Surrogate Models for the CMA Evolution Strategy.
    Evolutionary Computation. Roč. 27, č. 4 (2019), s. 665-697. ISSN 1063-6560. E-ISSN 1530-9304
    R&D Projects: GA ČR GA17-01251S; GA ČR(CZ) GA18-18080S
    Grant - others: GA MŠk(CZ) LM2015042
    Institutional support: RVO:67985807
    Keywords : Black-box optimization * CMA-ES * Gaussian processes * evolution strategies * surrogate modeling
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    Impact factor: 3.933, year: 2019
    Method of publishing: Limited access
    http://dx.doi.org/10.1162/evco_a_00244
    Permanent Link: http://hdl.handle.net/11104/0291157

               
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    0498868-afin.pdf1029.7 MBPublisher’s postprintrequire
    0498868-acc.pdf83.8 MBProofreading v.Author’s postprintrequire
    0498868subm.pdf122.7 MBSubmittedAuthor´s preprintopen-access
     
     
  10. 10.
    0478633 - ÚI 2018 RIV GB eng J - Journal Article
    Górecki, J. - Hofert, M. - Holeňa, Martin
    On Structure, Family and Parameter Estimation of Hierarchical Archimedean Copulas.
    Journal of Statistical Computation and Simulation. Roč. 87, č. 17 (2017), s. 3261-3324. ISSN 0094-9655. E-ISSN 1563-5163
    R&D Projects: GA ČR GA17-01251S
    Institutional support: RVO:67985807
    Keywords : copula estimation * goodness-of-fit * Hierarchical Archimedean copula * structure determination
    OECD category: Statistics and probability
    Impact factor: 0.869, year: 2017
    Permanent Link: http://hdl.handle.net/11104/0274688

               
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    a0478633.pdf911.5 MBPublisher’s postprintrequire
     
     

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