| An intelligence in our image: The risks of bias and errors in artificial intelligence OA Osoba, W Welser IV Rand Corporation, 2017 | 230 | 2017 |
| An open challenge to advance probabilistic forecasting for dengue epidemics MA Johansson, KM Apfeldorf, S Dobson, J Devita, AL Buczak, B Baugher, ... Proceedings of the National Academy of Sciences 116 (48), 24268-24274, 2019 | 101 | 2019 |
| Noise-enhanced convolutional neural networks K Audhkhasi, O Osoba, B Kosko Neural Networks 78, 15-23, 2016 | 86 | 2016 |
| Fuzzy cognitive maps of public support for insurgency and terrorism OA Osoba, B Kosko The journal of defense modeling and simulation 14 (1), 17-32, 2017 | 52 | 2017 |
| The risks of artificial intelligence to security and the future of work OA Osoba, W Welser RAND, 2017 | 48* | 2017 |
| Noise benefits in backpropagation and deep bidirectional pre-training K Audhkhasi, O Osoba, B Kosko The 2013 International Joint Conference on Neural Networks (IJCNN), 1-8, 2013 | 44 | 2013 |
| Noise-enhanced clustering and competitive learning algorithms O Osoba, B Kosko Neural Networks 37, 132-140, 2013 | 38 | 2013 |
| Deterrence in the age of thinking machines YH Wong, JM Yurchak, RW Button, A Frank, B Laird, OA Osoba, R Steeb, ... RAND Corporation Santa Monica, 2020 | 37 | 2020 |
| The noisy expectation–maximization algorithm O Osoba, S Mitaim, B Kosko Fluctuation and Noise Letters 12 (03), 1350012, 2013 | 37 | 2013 |
| Priority challenges for social and behavioral research and its modeling PK Davis, A O'Mahony, TR Gulden, OA Osoba, K Sieck RAND Corporation Santa Monica United States, 2018 | 33 | 2018 |
| Bayesian inference with adaptive fuzzy priors and likelihoods O Osoba, S Mitaim, B Kosko IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 41 …, 2011 | 33 | 2011 |
| Improving decision support for infectious disease prevention and control D Manheim, M Chamberlin, OA Osoba, R Vardavas, M Moore Santa Monica, CA: Rand Corporation, 2016 | 26 | 2016 |
| The noisy expectation-maximization algorithm for multiplicative noise injection O Osoba, B Kosko Fluctuation and Noise Letters 15 (01), 1650007, 2016 | 24 | 2016 |
| Improving privacy preservation policy in the modern information age JS Davis, O Osoba Health and Technology 9 (1), 65-75, 2019 | 21* | 2019 |
| Noisy hidden Markov models for speech recognition K Audhkhasi, O Osoba, B Kosko The 2013 international joint conference on neural networks (IJCNN), 1-6, 2013 | 20 | 2013 |
| Noise benefits in the expectation-maximization algorithm: NEM theorems and models O Osoba, S Mitaim, B Kosko The 2011 International Joint Conference on Neural Networks, 3178-3183, 2011 | 18 | 2011 |
| Beyond DAGs: modeling causal feedback with fuzzy cognitive maps O Osoba, B Kosko arXiv preprint arXiv:1906.11247, 2019 | 17 | 2019 |
| Noise can speed backpropagation learning and deep bidirectional pretraining B Kosko, K Audhkhasi, O Osoba Neural Networks 129, 359-384, 2020 | 14 | 2020 |
| Noise-boosted back propagation and deep learning neural networks K Audhkhasi, O Osoba, B Kosko US Patent App. 14/816,999, 2016 | 14 | 2016 |
| Algorithmic Equity: A Framework for Social Applications OA Osoba, B Boudreaux, JM Saunders, JL Irwin, PA Mueller, S Cherney RAND, 2019 | 11 | 2019 |
Bart KoskoProfessor of Electrical Engineering, University of Southern CaliforniaZweryfikowany adres z usc.edu
