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On the structure and values of betweenness centrality in dense betweenness-uniform graphs

GHANBARI, B., HARTMAN, David, JELÍNEK, V., POKORNÁ, Aneta, ŠÁMAL, R., VALTR, P. On the structure and values of betweenness centrality in dense betweenness-uniform graphs. In: KRÁĽ, D., NEŠETŘIL, J., eds. <em>EUROCOMB’23. Proceedings of the 12th European Conference on Combinatorics, Graph Theory and Applications</em>. Brno: MUNI Press, 2023, S. 478-484. E-ISSN 2788-3116<br>Dostupné z: doi:10.5817/CZ.MUNI.EUROCOMB23-066.

Autoři: B. Ghanbari , David Hartman , V. Jelínek , Aneta Pokorná , R. Šámal , P. Valtr

Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a data set from learning analytics

MARMOLEJO-RAMOS, F., TEJO, M., BRABEC, Marek, KUŽÍLEK, J., JOKSIMOVIC, S., KOVANOVIC, V., GONZÁLEZ, J., KNEIB, T., BÜHLMANN, P., KOOK, L., BRISEÑO-SÁNCHEZ, G., OSPINA, R. Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a data set from learning analytics. <em>Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery. </em> 2023, <b>13</b>(1), e1479. ISSN 1942-4787. E-ISSN 1942-4795<br>Dostupné z: doi:10.1002/widm.1479.

Autoři: F. Marmolejo-Ramos , M. Tejo , Marek Brabec , J. Kužílek , S. Joksimovic , V. Kovanovic , J. González , T. Kneib , P. Bühlmann , L. Kook , G. Briseño-Sánchez , R. Ospina

Energy Complexity Model for Convolutional Neural Networks

ŠÍMA, Jiří, VIDNEROVÁ, Petra, MRÁZEK, V. Energy Complexity Model for Convolutional Neural Networks. In: ILIADIS, L., PAPALEONIDAS, A., ANGELOV, P., JAYNE, C., eds. <em>Artificial Neural Networks and Machine Learning – ICANN 2023. Proceedings, Part X</em>. Cham: Springer, 2023, S. 186-198. Lecture Notes in Computer Science, 14263. ISBN 978-3-031-44203-2. ISSN 0302-9743<br>Dostupné z: doi:10.1007/978-3-031-44204-9_16.

Autoři: Jiří Šíma , Petra Vidnerová , V. Mrázek