| A note on the phase locking value and its properties S Aydore, D Pantazis, RM Leahy Neuroimage 74, 231-244, 2013 | 406 | 2013 |
| Differentially private query release through adaptive projection S Aydore, W Brown, M Kearns, K Kenthapadi, L Melis, A Roth, AA Siva International Conference on Machine Learning, 457-467, 2021 | 89 | 2021 |
| Classification of respiratory signals by linear analysis S Aydore, I Sen, YP Kahya, MK Mihcak 2009 Annual International Conference of the IEEE Engineering in Medicine and …, 2009 | 73 | 2009 |
| Romark: A robust watermarking system using adversarial training B Wen, S Aydore arXiv preprint arXiv:1910.01221, 2019 | 48 | 2019 |
| A robust variational autoencoder using beta divergence H Akrami, AA Joshi, J Li, S Aydöre, RM Leahy Knowledge-based systems 238, 107886, 2022 | 41 | 2022 |
| Adversarial robustness with non-uniform perturbations E Erdemir, J Bickford, L Melis, S Aydore Advances in Neural Information Processing Systems 34, 19147-19159, 2021 | 34 | 2021 |
| Private synthetic data for multitask learning and marginal queries G Vietri, C Archambeau, S Aydore, W Brown, M Kearns, A Roth, A Siva, ... Advances in Neural Information Processing Systems 35, 18282-18295, 2022 | 32 | 2022 |
| On temporal connectivity of PFC via Gauss-Markov modeling of fNIRS signals S Aydore, MK Mihcak, K Ciftci, A Akin IEEE transactions on biomedical engineering 57 (3), 761-768, 2009 | 32 | 2009 |
| Brain lesion detection using a robust variational autoencoder and transfer learning H Akrami, AA Joshi, J Li, S Aydore, RM Leahy 2020 IEEE 17th international symposium on biomedical imaging (ISBI), 786-790, 2020 | 27 | 2020 |
| Dynamic local regret for non-convex online forecasting S Aydore, T Zhu, DP Foster Advances in neural information processing systems 32, 2019 | 27 | 2019 |
| Robust variational autoencoder H Akrami, AA Joshi, J Li, S Aydore, RM Leahy arXiv preprint arXiv:1905.09961, 2019 | 26 | 2019 |
| Robust variational autoencoder for tabular data with beta divergence H Akrami, S Aydore, RM Leahy, AA Joshi arXiv preprint arXiv:2006.08204, 2020 | 21 | 2020 |
| Dropcluster: A structured dropout for convolutional networks L Chen, P Gautier, S Aydore arXiv preprint arXiv:2002.02997, 2020 | 13 | 2020 |
| Feature grouping as a stochastic regularizer for high-dimensional structured data S Aydore, B Thirion, G Varoquaux International Conference on Machine Learning, 385-394, 2019 | 10 | 2019 |
| Membership inference attacks on diffusion models via quantile regression S Tang, ZS Wu, S Aydore, M Kearns, A Roth arXiv preprint arXiv:2312.05140, 2023 | 7 | 2023 |
| Deep quantile regression for uncertainty estimation in unsupervised and supervised lesion detection H Akrami, AA Joshi, S Aydöre, RM Leahy The journal of machine learning for biomedical imaging 1, 008, 2022 | 7 | 2022 |
| Quantile regression for uncertainty estimation in vaes with applications to brain lesion detection H Akrami, A Joshi, S Aydore, R Leahy International Conference on Information Processing in Medical Imaging, 689-700, 2021 | 7 | 2021 |
| Detecting anomalous events from categorical data using autoencoders S Aydore, B Coskun, L Melis US Patent 11,537,902, 2022 | 6 | 2022 |
| Addressing variance shrinkage in variational autoencoders using quantile regression H Akrami, AA Joshi, S Aydore, RM Leahy arXiv preprint arXiv:2010.09042, 2020 | 6 | 2020 |
| Improved differentially private regression via gradient boosting S Tang, S Aydore, M Kearns, S Rho, A Roth, Y Wang, YX Wang, ZS Wu 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 33-56, 2024 | 5 | 2024 |
Ata AkinAcıbadem UniversityPatvirtintas el. paštas acibadem.edu.tr