| Residual and plain convolutional neural networks for 3D brain MRI classification S Korolev, A Safiullin, M Belyaev, Y Dodonova 2017 IEEE 14th international symposium on biomedical imaging (ISBI 2017 …, 2017 | 465 | 2017 |
| Processing speed and intelligence as predictors of school achievement: Mediation or unique contribution? YA Dodonova, YS Dodonov Intelligence 40 (2), 163-171, 2012 | 52 | 2012 |
| Faster on easy items, more accurate on difficult ones: Cognitive ability and performance on a task of varying difficulty YA Dodonova, YS Dodonov Intelligence 41 (1), 1-10, 2013 | 43 | 2013 |
| Is there any evidence of historical slowing of reaction time? No, unless we compare apples and oranges YA Dodonova, YS Dodonov Intelligence 41 (5), 674-687, 2013 | 32 | 2013 |
| Robust measures of central tendency: weighting as a possible alternative to trimming in response-time data analysis YS Dodonov, YA Dodonova Psikhologicheskie Issledovaniya 5 (19), 2011 | 29 | 2011 |
| Speed of emotional information processing and emotional intelligence YA Dodonova, YS Dodonov International Journal of Psychology 47 (6), 429-437, 2012 | 28 | 2012 |
| Response time analysis in cognitive tasks with increasing difficulty YS Dodonov, YA Dodonova Intelligence 40 (5), 379-394, 2012 | 26 | 2012 |
| Basic processes of cognitive development: missing component in Piaget's Theory YS Dodonov, YA Dodonova Procedia-Social and Behavioral Sciences 30, 1345-1349, 2011 | 17 | 2011 |
| Classification of normal and pathological brain networks based on similarity in graph partitions A Kurmukov, Y Dodonova, L Zhukov 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW …, 2016 | 13 | 2016 |
| Classifying phenotypes based on the community structure of human brain networks A Kurmukov, M Ananyeva, Y Dodonova, B Gutman, J Faskowitz, ... Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging …, 2017 | 12 | 2017 |
| Classification of structural brain networks based on information divergence of graph spectra MB Yulia Dodonova, Sergey Korolev, Anna Tkachev, Dmitry Petrov, Leonid Zhukov Machine Learning for Signal Processing (MLSP), 2016 IEEE 26th International …, 2016 | 12* | 2016 |
| Boosting connectome classification via combination of geometric and topological normalizations D Petrov, Y Dodonova, L Zhukov, M Belyaev 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI), 1-4, 2016 | 12 | 2016 |
| 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) S Korolev, A Safiullin, M Belyaev, Y Dodonova | 11 | 2017 |
| Machine learning application to human brain network studies: A kernel approach A Kurmukov, Y Dodonova, LE Zhukov Models, Algorithms, and Technologies for Network Analysis: NET 2016, Nizhny …, 2017 | 6* | 2017 |
| Kernel classification of connectomes based on earth mover's distance between graph spectra Y Dodonova, M Belyaev, A Tkachev, D Petrov, L Zhukov arXiv preprint arXiv:1611.08812, 2016 | 6 | 2016 |
| Topological modules of human brain networks are anatomically embedded: evidence from modularity analysis at multiple scales A Kurmukov, Y Dodonova, M Burova, A Mussabayeva, D Petrov, ... Computational Aspects and Applications in Large-Scale Networks: NET 2017 …, 2018 | 5 | 2018 |
| Emotional sensitivity measurement in cognitive tasks with emotional stimuli YA Dodonova, YS Dodonov Procedia-Social and Behavioral Sciences 5, 1596-1600, 2010 | 5 | 2010 |
| Differences in structural connectomes between typically developing and autism groups D Petrov, Y Dodonova, L Zhukov Proceedings of the 39th interdisciplinary school-conference of the IPPI RAS …, 2015 | 4 | 2015 |
| Image registration and predictive modeling: learning the metric on the space of diffeomorphisms A Mussabayeva, A Kroshnin, A Kurmukov, Y Denisova, L Shen, S Cong, ... Shape in Medical Imaging: International Workshop, ShapeMI 2018, Held in …, 2018 | 2 | 2018 |
| A latent growth curve (LGC) analysis to model task demands and the Worst Performance Rule simultaneously N Borter, S Troche, Y Dodonova, T Rammsayer | 2 | 2014 |
