Publications
2024
Adversarially robust spiking neural networks through conversion
O. Özdenizci, R. Legenstein,
Transactions on Machine Learning Research (TMLR), 2024. [PDF / Code]Preserving real-world robustness of neural networks under sparsity constraints
J. V. Gritsch, R. Legenstein, O. Özdenizci,
European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), 2024. [PDF / Code]AI-Infused Design: Merging parametric models for architectural design
A. Sebestyen, O. Özdenizci, R. Legenstein, U. Hirschberg,
42nd Education and Research in Computer Aided Architectural Design in Europe Conference (eCAADe), Nicosia, Cyprus, 2024. [PDF]
2023
Restoring vision in adverse weather conditions with patch-based denoising diffusion models
O. Özdenizci, R. Legenstein,
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023. [PDF / Code / Slides]Memory-dependent computation and learning in spiking neural networks through Hebbian plasticity
T. Limbacher, O. Özdenizci, R. Legenstein,
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023. [PDF / Code]Interaction of generalization and out-of-distribution detection capabilities in deep neural networks
F. J. Klaiber Aboitiz, R. Legenstein, O. Özdenizci,
32nd International Conference on Artificial Neural Networks (ICANN), Crete, Greece, 2023. [PDF]Generating conceptual architectural 3D geometries with denoising diffusion models
A. Sebestyen, O. Özdenizci, R. Legenstein, U. Hirschberg,
41st Education and Research in Computer Aided Architectural Design in Europe Conference (eCAADe), Graz, Austria, 2023. [PDF]TS-MoCo: Time-series momentum contrast for self-supervised physiological representation learning
P. Hallgarten, D. Bethge, O. Özdenizci, T. Grosse-Puppendahl, E. Kasneci,
31st European Signal Processing Conference (EUSIPCO), Helsinki, Finland, 2023. [PDF]
2022
Improving robustness against stealthy weight bit-flip attacks by output code matching
O. Özdenizci, R. Legenstein,
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [PDF / Code / Slides]EEG2Vec: Learning affective EEG representations via variational autoencoders
D. Bethge, P. Hallgarten, T. Grosse-Puppendahl, M. Kari, L Chuang, O. Özdenizci, A. Schmidt,
IEEE International Conference on Systems, Man, and Cybernetics (SMC), Prague, Czech Republic, 2022. [PDF]Exploiting multiple EEG data domains with adversarial learning
D. Bethge, P. Hallgarten, O. Özdenizci, R. Mikut, A. Schmidt, T. Grosse-Puppendahl,
IEEE Engineering in Medicine and Biology Conference (EMBC), Glasgow, Scotland, UK, 2022. [PDF]Domain-invariant representation learning from EEG with private encoders
D. Bethge, P. Hallgarten, T. Grosse-Puppendahl, M. Kari, R. Mikut, A. Schmidt, O. Özdenizci,
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Singapore, 2022. [PDF]
2021
Training adversarially robust sparse networks via Bayesian connectivity sampling
O. Özdenizci, R. Legenstein,
International Conference on Machine Learning (ICML), 2021. [PDF / Code / Talk / Slides / Poster]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, vol 25(8), pp 2928-2937, 2021. [PDF]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. [PDF]Stochastic mutual information gradient estimation for dimensionality reduction networks
O. Özdenizci, D. Erdoğmuş,
Information Sciences, vol 570, pp 298-305, 2021. [PDF]EEG-based texture roughness classification in active tactile exploration with invariant representation learning networks
O. Özdenizci, S. Eldeeb, A. Demir, D. Erdoğmuş, M. Akçakaya,
Biomedical Signal Processing and Control, vol 67, pp 102507, 2021. [PDF]
2020
Learning invariant representations from EEG via adversarial inference
O. Özdenizci, Y. Wang, T. Koike-Akino, D. Erdoğmuş,
IEEE Access, vol 8, pp 27074-27085, 2020. [PDF / Code]Disentangled adversarial autoencoder for subject-invariant physiological feature extraction
M. Han, O. Özdenizci, Y. Wang, T. Koike-Akino, D. Erdoğmuş,
IEEE Signal Processing Letters, vol 27, pp 1565-1569, 2020. [PDF]Disentangled adversarial transfer learning for physiological biosignals
M. Han, O. Özdenizci, Y. Wang, T. Koike-Akino, D. Erdoğmuş,
IEEE Engineering in Medicine and Biology Conference (EMBC), 2020. [PDF]
2019
Information theoretic feature transformation learning for brain interfaces
O. Özdenizci, D. Erdoğmuş,
IEEE Transactions on Biomedical Engineering, vol 67(1), pp 69-78, 2019. [PDF / Code]Adversarial deep learning in EEG biometrics
O. Özdenizci, Y. Wang, T. Koike-Akino, D. Erdoğmuş,
IEEE Signal Processing Letters, vol 26(5), pp 710-714, 2019. [PDF / Code]Neural signatures of motor skill in the resting brain
O. Özdenizci, T. Meyer, F. Wichmann, J. Peters, B. Schölkopf, M. Grosse-Wentrup,
IEEE International Conference on Systems, Man, and Cybernetics (SMC), Bari, Italy, 2019. [PDF]Adversarial feature learning in brain interfacing: an experimental study on eliminating drowsiness effects
O. Özdenizci, B. Oken, T. Memmott, M. Fried-Oken, D. Erdoğmuş,
8th Graz Brain-Computer Interface Conference, Graz, Austria, 2019. [PDF]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), San Francisco, USA, 2019. [PDF / Code]
2018
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, S. Ioannidis, M. S. Goodwin,
IEEE Engineering in Medicine and Biology Conference (EMBC), Honolulu, USA, 2018. [PDF]Hierarchical graphical models for context-aware hybrid brain-machine interfaces
O. Özdenizci, S. Y. Günay, F. Quivira, D. Erdoğmuş,
IEEE Engineering in Medicine and Biology Conference (EMBC), Honolulu, USA, 2018. [PDF]Predicting imminent aggression onset in minimally-verbal youth with autism spectrum disorder using preceding physiological signals
M. S. Goodwin, O. Özdenizci, C. Cumpanasoiu, P. Tian, Y. Guo, A. Stedman, C. Peura, C. Mazefsky, M. Siegel, D. Erdoğmuş, S. Ioannidis,
12th EAI International Conference on Pervasive Computing Technologies for Healthcare, New York, USA, 2018. [PDF]
2017
Electroencephalographic identifiers of motor adaptation learning
O. Özdenizci, M. Yalçın, A. Erdoğan, V. Patoğlu, M. Grosse-Wentrup, M. Çetin,
Journal of Neural Engineering, vol 14(4), pp 046027, 2017. [PDF]Information theoretic feature projection for single-trial brain-computer interfaces
O. Özdenizci, F. Quivira, D. Erdoğmuş,
IEEE International Workshop on Machine Learning for Signal Processing (MLSP), Tokyo, Japan, 2017. [PDF]Personalized brain-computer interface models for motor rehabilitation
A. A. Mastakouri, S. Weichwald, O. Özdenizci, T. Meyer, B. Schölkopf, M. Grosse-Wentrup,
IEEE International Conference on Systems, Man, and Cybernetics (SMC), Banff, Canada, 2017. [PDF]Correlations of motor adaptation learning and modulation of resting-state sensorimotor EEG activity
O. Özdenizci, M. Yalçın, A. Erdoğan, V. Patoğlu, M. Grosse-Wentrup, M. Çetin,
7th Graz Brain-Computer Interface Conference, Graz, Austria, 2017. [PDF]Pre-movement EEG low beta power is modulated with motor adaptation learning
O. Özdenizci, M. Yalçın, A. Erdoğan, V. Patoğlu, M. Grosse-Wentrup, M. Çetin,
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, USA, 2017. [PDF]
2016
- Resting-state EEG correlates of motor learning performance in a force-field adaptation task
O. Özdenizci, M. Yalçın, A. Erdoğan, V. Patoğlu, M. Grosse-Wentrup, M. Çetin,
IEEE Signal Processing and Communications Applications Conference (SIU), Ankara, Turkey, 2016. [PDF]
2015
Causal interpretation rules for encoding and decoding models in neuroimaging
S. Weichwald, T. Meyer, O. Özdenizci, B. Schölkopf, T. Ball, M. Grosse-Wentrup,
NeuroImage, vol 110, pp 48-59, 2015. [PDF]Adaptive alpha neurofeedback on parieto-occipital cortex for motor learning performance
O. Özdenizci, T. Meyer, M. Çetin, M. Grosse-Wentrup,
IEEE Signal Processing and Communications Applications Conference (SIU), Malatya, Turkey, 2015. [PDF]
2014
- Towards neurofeedback training of associative brain areas for stroke rehabilitation
O. Özdenizci, T. Meyer, M. Çetin, M. Grosse-Wentrup,
6th Graz Brain-Computer Interface Conference, Graz, Austria, 2014. [PDF]
Theses
Statistical Learning and Inference in Neural Signal Processing: Applications to Brain Interfaces
O. Özdenizci,
Ph.D. Dissertation, Northeastern University, Boston, MA, USA, April 2020. [PDF]Identifying Neural Correlates of Motor Adaptation Learning for BCI-Assisted Stroke Rehabilitation
O. Özdenizci,
MSc. Thesis, Sabancı University, Istanbul, Turkey, August 2016. [PDF]Neurofeedback Training via Brain-Computer Interfaces for Motor Learning Performance
O. Özdenizci,
BSc. Senior Project, Sabancı University, Istanbul, Turkey, June 2014.