Search results
- 1.0585428 - ÚI 2025 RIV NL J - Journal Article
Arinyo i Prats, Andreu - López-Madrona, V. J. - Paluš, Milan
Lead/Lag directionality is not generally equivalent to causality in nonlinear systems: Comparison of phase slope index and conditional mutual information.
Neuroimage. Roč. 292, 15 April 2024 (2024), č. článku 120610. ISSN 1053-8119. E-ISSN 1095-9572
R&D Projects: GA ČR(CZ) GF21-14727K
Institutional support: RVO:67985807
Keywords : Coupling directionality * Cross-frequency coupling * Conditional mutual information * Phase slope index * EEG * Nonlinear systems
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impact factor: 5.7, year: 2022
Method of publishing: Open access
https://doi.org/10.1016/j.neuroimage.2024.120610
Permanent Link: https://hdl.handle.net/11104/0353138File Download Size Commentary Version Access 0585428-oaf.pdf 1 1.5 MB OA CC BY 4.0 Publisher’s postprint open-access - 2.0573671 - ÚI 2024 RIV SK eng C - Conference Paper (international conference)
Bhattacharjee, Madhurima - Kathpalia, Aditi - Brunovský, M. - Paluš, Milan
Phase-based Causality Analysis of EEG in Treatment of Major Depressive Disorder.
2023 14th International Conference on Measurement. Proceedings. Bratislava: Institute of Measurement Science, SAS / IEEE, 2023 - (Dvurečenskij, A.; Maňka, J.; Švehlíková, J.; Witkovský, V.), s. 84-87. ISBN 979-8-3503-1218-8.
[MEASUREMENT 2023: International Conference on Measurement /14./. Smolenice (SK), 29.05.2023-31.05.2023]
R&D Projects: GA ČR(CZ) GF21-14727K
Institutional support: RVO:67985807
Keywords : Brain Connectivity * Phase-Based Causality * Eeg * Major Depressive Disorder * Mutual Information
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
https://dx.doi.org/10.23919/MEASUREMENT59122.2023.10164427
Permanent Link: https://hdl.handle.net/11104/0344053 - 3.0566845 - ÚFCH JH 2024 RIV NL eng J - Journal Article
Golub, Pavlo - Antalík, Andrej - Beran, Pavel - Brabec, Jiří
Mutual information prediction for strongly correlated systems.
Chemical Physics Letters. Roč. 813, FEB 2023 (2023), č. článku 140297. ISSN 0009-2614. E-ISSN 1873-4448
R&D Projects: GA ČR(CZ) GJ19-13126Y
Institutional support: RVO:61388955
Keywords : DMRG * Quantum chemistry * Mutual information * Strong correlation * Machine learning
OECD category: Physical chemistry
Impact factor: 2.8, year: 2022
Method of publishing: Limited access
Permanent Link: https://hdl.handle.net/11104/0338119File Download Size Commentary Version Access 0566845.pdf 1 2.2 MB Publisher’s postprint require - 4.0554542 - ÚMG 2022 RIV GB eng J - Journal Article
Čmelo, I. - Voršilák, Milan - Svozil, Daniel
Profiling and analysis of chemical compounds using pointwise mutual information.
Journal of Cheminformatics. Roč. 13, č. 1 (2021), č. článku 3. ISSN 1758-2946. E-ISSN 1758-2946
R&D Projects: GA MŠMT(CZ) LM2018130
Research Infrastructure: CZ-OPENSCREEN III - 90130
Institutional support: RVO:68378050
Keywords : Hashed fingerprint * Structural key * Information theory * Pointwise mutual information * Synthetic accessibility
OECD category: Biochemistry and molecular biology
Impact factor: 8.489, year: 2021
Method of publishing: Open access
https://jcheminf.biomedcentral.com/articles/10.1186/s13321-020-00483-y
Permanent Link: http://hdl.handle.net/11104/0329252 - 5.0545816 - ÚI 2022 CH eng J - Journal Article
Billings, Jacob - Thompson, G. J. - Pan, W.J. - Magnuson, M.E. - Medda, A. - Keilholz, S.
Disentangling Multispectral Functional Connectivity With Wavelets.
Frontiers in Neuroscience. Roč. 12 (2018), č. článku 812. E-ISSN 1662-453X
Keywords : resting-state * human brain * fmri * networks * signal * mri * dynamics * cortex * decomposition * fluctuations * resting state * functional magnetic resonance imaging * functional connectivity * wavelet packet transform * mutual information * clustering
Impact factor: 3.648, year: 2018
Permanent Link: http://hdl.handle.net/11104/0322461 - 6.0520385 - ÚI 2021 RIV US eng J - Journal Article
Kořenek, Jakub - Hlinka, Jaroslav
Causal network discovery by iterative conditioning: Comparison of algorithms.
Chaos. Roč. 30, č. 1 (2020), č. článku 013117. ISSN 1054-1500. E-ISSN 1089-7682
R&D Projects: GA MZd(CZ) NV15-29835A; GA MZd(CZ) NV15-33250A; GA MZd(CZ) NV17-28427A; GA ČR(CZ) GA19-16066S; GA ČR(CZ) GA19-11753S
Grant - others:GA MŠk(CZ) LO1611
Institutional support: RVO:67985807
Keywords : causality inference * complex networks * transfer entropy * conditional mutual information * Granger causality
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impact factor: 3.642, year: 2020
Method of publishing: Limited access
http://dx.doi.org/10.1063/1.5115267
Permanent Link: http://hdl.handle.net/11104/0305065 - 7.0511450 - ÚTIA 2020 RIV IT eng J - Journal Article
Uglickich, Evženie - Nagy, Ivan - Vlčková, D.
Comparing clusterings using combination of the kappa statistic and entropy-based measure.
Metron. Roč. 77, č. 3 (2019), s. 253-270. ISSN 0026-1424
R&D Projects: GA MŠMT(CZ) 8A17006
Institutional support: RVO:67985556
Keywords : Comparing clusterings * Clusters agreement * kappa max statistic * Normalized mutual information
OECD category: Statistics and probability
Method of publishing: Limited access
http://library.utia.cas.cz/separaty/2019/ZS/uglickich-0511450.pdf https://link.springer.com/article/10.1007%2Fs40300-019-00162-5
Permanent Link: http://hdl.handle.net/11104/0302474 - 8.0510483 - ÚTIA 2020 RIV CH eng C - Conference Paper (international conference)
Haindl, Michal - Havlíček, Michal
Mutual Information-Based Texture Spectral Similarity Criterion.
Advances in Visual Computing : 14th International Symposium on Visual Computing (ISVC 2019). Cham: Springer, 2019 - (Bebis, G.; Boyle, R.; Parvin, B.; Koracin, D.), s. 302-314, č. článku 23. Lecture Notes in Computer Science, 11844. ISBN 978-3-030-33719-3. ISSN 0302-9743. E-ISSN 1611-3349.
[International Symposium on Visual Computing (ISVC 2019) /14./. Lake Tahoe (US), 07.10.2019-09.10.2019]
R&D Projects: GA ČR(CZ) GA19-12340S
Institutional support: RVO:67985556
Keywords : spectral similarity criterion * Bidirectional Texture Functions * texture * mutual information
OECD category: Automation and control systems
http://library.utia.cas.cz/separaty/2019/RO/haindl-0510483.pdf
Permanent Link: http://hdl.handle.net/11104/0302679 - 9.0509811 - ÚI 2020 RIV CZ eng L4 - Software
Jajcay, Nikola
pyCliTS.
Internal code: pyCliTS ; 2019
Technical parameters: PyCliTS je pythonový balíček licencovaný pod MIT. Momentálně funguje pro verzi Pythonu 2.7. Pro optimální funkcionalitu se doporučují další balíčky, jejichž seznam je uveden v rámci README: https://github.com/jajcayn/pyclits/blob/master/README.rst
Economic parameters: Balíček umožňuje: manipulaci s daty (časové a prostorové, interpolace, odečtení klimatologického cyklu = anomalizace, normalizace, filtrování, podvzorkování atd.) - výpočet vlnkové transformace [CCWT] - konstruování časoprostorových surogátních dat pomocí přístupu Monte-Carlo [Fourierova transformace, amplitudově upravená FT, iterativní amplituda upravená FT, autoregresivní model VAR (p), multiškálová metoda] - výpočet Singular Spectrum Analysis - výpočet vzájemných informací a podmíněných vzájemných informací [různé algoritmy] - konstruování empirického modelu z časoprostorových dat založených na myšlence LIM [lineární inverzní modelování].
Institutional support: RVO:67985807
Keywords : python * climate time series * CCWT * surrogates * mutual information * modelling * klimatické časové řady * CCWT * vzájemná informace * surogáty * modelování
OECD category: Meteorology and atmospheric sciences
https://github.com/jajcayn/pyclits
Permanent Link: http://hdl.handle.net/11104/0300430 - 10.0497540 - ÚTIA 2019 RIV JP eng C - Conference Paper (international conference)
Kratochvíl, Václav - Jiroušek, Radim - Lee, T. R.
Efficient implementation of compositional models for data mining.
Proceedings of the 21st Czech-Japan Seminar od Data Analysis and Decision Making. Japan: Aoyama Gakuin University, Japan, 2018 - (Sung, S.; Vlach, M.), s. 80-87. ISBN 978-80-7464-932-5.
[The 21st Czech-Japan Seminar on Data Analysis and Decision Making. Kamakura (JP), 23.11.2018-26.11.2018]
R&D Projects: GA ČR(CZ) GA16-12010S
Grant - others:AV ČR(CZ) MOST-18-04
Program: Bilaterální spolupráce
Institutional support: RVO:67985556
Keywords : data mining * mutual information * compositional models * conditional independence * probability theory
OECD category: Automation and control systems
http://library.utia.cas.cz/separaty/2018/MTR/kratochvil-0497540.pdf
Permanent Link: http://hdl.handle.net/11104/0291220