| Partitioning the Right Ventricle into 15 Segments and Decomposing its Motion using 3D Echocardiography-based Models: The Updated ReVISION Method M Tokodi, L Staub, Á Budai, BK Lakatos, M Csákvári, FI Suhai, L Szabó, ... Frontiers in Cardiovascular Medicine 8, 24, 0 | 39 | |
| Towards reasoning based representations: Deep Consistence Seeking Machine A Lőrincz, M Csákvári, Á Fóthi, ZÁ Milacski, A Sárkány, Z Tősér Cognitive Systems Research 47, 92-108, 2018 | 9 | 2018 |
| Cognitive Deep Machine Can Train Itself A Lőrincz, M Csákvári, Á Fóthi, ZÁ Milacski, A Sárkány, Z Tősér arXiv preprint arXiv:1612.00745, 2016 | 3 | 2016 |
| Exploring sex-specific patterns of mortality predictors among patients undergoing cardiac resynchronization therapy: a machine learning approach M Tokodi, A Behon, ED Merkel, A Kovacs, Z Toser, A Sarkany, M Csakvari, ... European Heart Journal 41 (Supplement_2), ehaa946. 0996, 2020 | 2 | 2020 |
| ASSOCIATION BETWEEN BIVENTRICULAR MECHANICAL PATTERN AND EXERCISE CAPACITY IN ATHLETES: MACHINE LEARNING BASED PREDICTION OF PEAK OXYGEN UPTAKE M Tokodi, BK Lakatos, Z Tősér, M Csákvári, A Fábián, M Babity, C Bognár, ... Journal of the American College of Cardiology 75 (11_Supplement_1), 1562-1562, 2020 | | 2020 |
| Combining Common Sense Rules and Machine Learning to Understand Object Manipulation A Sárkány, M Csákvári, M Olasz Acta Cybernetica 24 (1), 157-172, 2019 | | 2019 |
| Towards the understanding of object manipulations by means of combining common sense rules and deep networks M Csákvári, A Sárkány THE 11TH CONFERENCE OF PHD STUDENTS IN COMPUTER SCIENCE, 118, 2018 | | 2018 |
