| Introduction to Deep Learning: from logical calculus to artificial intelligence S Skansi Springer, 2018 | 411 | 2018 |
| Convolutional neural networks S Skansi, S Skansi Introduction to Deep Learning: from logical calculus to artificial …, 2018 | 16 | 2018 |
| A method for MBTI classification based on impact of class components N Cerkez, B Vrdoljak, S Skansi IEEE Access 9, 146550-146567, 2021 | 14 | 2021 |
| Autoencoders S Skansi, S Skansi Introduction to Deep Learning: From Logical Calculus to Artificial …, 2018 | 11 | 2018 |
| Evaluation of structural hyperparameters for text classification with LSTM networks M Frković, N Čerkez, B Vrdoljak, S Skansi 2020 43rd International Convention on Information, Communication and …, 2020 | 9 | 2020 |
| Machine learning basics S Skansi, S Skansi Introduction to Deep Learning: From Logical Calculus to Artificial …, 2018 | 8 | 2018 |
| Guide to Deep Learning Basics S Skansi Springer International Publishing, 2020 | 7 | 2020 |
| Introduction to Deep Learning; Undergraduate Topics in Computer Science S Skansi Springer International Publishing: Cham, Switzerland, 2018 | 7 | 2018 |
| The role of process ontology in cybernetics S Skansi, K Šekrst Synthesis philosophica 36 (2), 461-469, 2021 | 4 | 2021 |
| A Lost Croatian Cybernetic Machine Translation Program S Skansi, L Mršić, I Skelac Guide to Deep Learning Basics: Logical, Historical and Philosophical …, 2020 | 4 | 2020 |
| Recurrent neural networks S Skansi, S Skansi Introduction to Deep Learning: From Logical Calculus to Artificial …, 2018 | 4 | 2018 |
| Feedforward neural networks S Skansi, S Skansi Introduction to Deep Learning: From Logical Calculus to Artificial …, 2018 | 4 | 2018 |
| A constructive proof of cut elimination for a system of full second order logic S Skansi arXiv preprint arXiv:1606.01763, 2016 | 4 | 2016 |
| Analyzing affective states using acoustic and linguistic features B Dropuljic, S Skansi, R Kopal Central European Conference on Information and Intelligent Systems, 201, 2016 | 4 | 2016 |
| Umjetna inteligencija i kompatibilizam: mogućnost postanka slobodnog uma u determiniranom tijelu S Skansi Filozofska istraživanja 35 (03/139), 407-414, 2015 | 4 | 2015 |
| Metodologija estimacije emocionalnih stanja na temelju akustičkih značajki govora B Dropuljić, S Skansi, L Mršić International Journal of Digital Technology & Economy 1 (1), 53-74, 2016 | 3 | 2016 |
| An overview of different neural network architectures S Skansi, S Skansi Introduction to Deep Learning: From Logical Calculus to Artificial …, 2018 | 2 | 2018 |
| From logic to cognitive science S Skansi, S Skansi Introduction to Deep Learning: From Logical Calculus to Artificial …, 2018 | 2 | 2018 |
| Croatian emotional speech analyses on a basis of acoustic and linguistic features B Dropuljić, S Skansi, R Kopal International Journal of Digital Technology & Economy 1 (2), 85-96, 2016 | 2 | 2016 |
| Machine learning and essentialism K Šekrst, S Skansi Philosophical Problems in Science (Zagadnienia Filozoficzne w Nauce), 171-196, 2022 | 1 | 2022 |
Davor LaucThe Chair of Logic, Faculty of Humanities and Social Sciences, University of ZagrebVerified email at ffzg.unizg.hr
