| Causal interpretation rules for encoding and decoding models in neuroimaging S Weichwald, T Meyer, O Özdenizci, B Schölkopf, T Ball, ... NeuroImage 110, 48-59, 2015 | 109 | 2015 |
| Adversarial deep learning in EEG biometrics O Özdenizci, Y Wang, T Koike-Akino, D Erdoğmuş IEEE Signal Processing Letters 26 (5), 710-714, 2019 | 86 | 2019 |
| Learning invariant representations from EEG via adversarial inference O Özdenizci, Y Wang, T Koike-Akino, D Erdoğmuş IEEE Access 8, 27074-27085, 2020 | 76 | 2020 |
| Transfer learning in brain-computer interfaces with adversarial variational autoencoders O Özdenizci, Y Wang, T Koike-Akino, D Erdoğmuş 9th International IEEE/EMBS Conference on Neural Engineering (NER), 2019 | 65 | 2019 |
| Restoring vision in adverse weather conditions with patch-based denoising diffusion models O Özdenizci, R Legenstein IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 36 | 2023 |
| Electroencephalographic identifiers of motor adaptation learning O Özdenizci, M Yalçın, A Erdoğan, V Patoğlu, M Grosse-Wentrup, M Çetin Journal of Neural Engineering 14 (4), 2017 | 31 | 2017 |
| Predicting imminent aggression onset in minimally-verbal youth with autism spectrum disorder using preceding physiological signals MS Goodwin, O Özdenizci, C Cumpanasoiu, P Tian, Y Guo, A Stedman, ... 12th EAI International Conference on Pervasive Computing Technologies for …, 2018 | 26 | 2018 |
| Disentangled adversarial autoencoder for subject-invariant physiological feature extraction M Han, O Özdenizci, Y Wang, T Koike-Akino, D Erdoğmuş IEEE Signal Processing Letters 27, 1565-1569, 2020 | 23 | 2020 |
| Domain-invariant representation learning from EEG with private encoders D Bethge, P Hallgarten, T Grosse-Puppendahl, M Kari, R Mikut, A Schmidt, ... ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 17 | 2022 |
| Training adversarially robust sparse networks via Bayesian connectivity sampling O Özdenizci, R Legenstein International Conference on Machine Learning (ICML), 8314-8324, 2021 | 17 | 2021 |
| EEG2Vec: Learning affective EEG representations via variational autoencoders D Bethge, P Hallgarten, T Grosse-Puppendahl, M Kari, LL Chuang, ... IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2022 | 15 | 2022 |
| Information theoretic feature transformation learning for brain interfaces O Özdenizci, D Erdoğmuş IEEE Transactions on Biomedical Engineering 67 (1), 69-78, 2019 | 15 | 2019 |
| Stochastic mutual information gradient estimation for dimensionality reduction networks O Özdenizci, D Erdoğmuş Information Sciences 570, 298-305, 2021 | 14 | 2021 |
| Time-series prediction of proximal aggression onset in minimally-verbal youth with autism spectrum disorder using physiological biosignals O Özdenizci, C Cumpanasoiu, C Mazefsky, M Siegel, D Erdoğmuş, ... 40th Annual International Conference of the IEEE Engineering in Medicine and …, 2018 | 14 | 2018 |
| Hierarchical graphical models for context-aware hybrid brain-machine interfaces O Özdenizci, SY Gunay, F Quivira, D Erdoğmuş 40th Annual International Conference of the IEEE Engineering in Medicine and …, 2018 | 13 | 2018 |
| Universal physiological representation learning with soft-disentangled rateless autoencoders M Han, O Özdenizci, T Koike-Akino, Y Wang, D Erdoğmuş IEEE Journal of Biomedical and Health Informatics 25 (8), 2928-2937, 2021 | 10 | 2021 |
| Exploiting multiple EEG data domains with adversarial learning D Bethge, P Hallgarten, O Özdenizci, R Mikut, A Schmidt, ... 44th Annual International Conference of the IEEE Engineering in Medicine and …, 2022 | 9 | 2022 |
| Personalized brain-computer interface models for motor rehabilitation AA Mastakouri, S Weichwald, O Özdenizci, T Meyer, B Schölkopf, ... IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2017 | 9 | 2017 |
| Towards neurofeedback training of associative brain areas for stroke rehabilitation O Özdenizci, T Meyer, M Çetin, M Grosse-Wentrup 6th International Brain-Computer Interface Conference 2014, 2014 | 7 | 2014 |
| On the use of generative deep neural networks to synthesize artificial multichannel EEG signals O Özdenizci, D Erdoğmuş 10th International IEEE/EMBS Conference on Neural Engineering (NER), 2021 | 6 | 2021 |
Deniz ErdogmusProfessor of ECE, Northeastern UniversityVerified email at ece.neu.edu
