102 citations · 163 across the 13 of their papers we have counts for
15 papers
Relational Abstractions for Spatial Reasoning with Diffusion Models
Ana Ezquerro, Ozan Özdenizci
Diffusion models excel at image synthesis, but they remain limited in their ability to reliably satisfy structured spatial reasoning constraints. In conditional data distribution m…
Adversarially Robust Spiking Neural Networks with Sparse Connectivity
Mathias Schmolli, Maximilian Baronig, Robert Legenstein +1
Deployment of deep neural networks in resource-constrained embedded systems requires innovative algorithmic solutions to facilitate their energy and memory efficiency. To further e…
Adversarially Robust Spiking Neural Networks Through Conversion
Ozan Özdenizci, Robert Legenstein
Spiking neural networks (SNNs) provide an energy-efficient alternative to a variety of artificial neural network (ANN) based AI applications. As the progress in neuromorphic comput…
Memory-enriched computation and learning in spiking neural networks through Hebbian plasticity
Thomas Limbacher, Ozan Özdenizci, Robert Legenstein
Memory is a key component of biological neural systems that enables the retention of information over a huge range of temporal scales, ranging from hundreds of milliseconds up to y…
Exploiting Multiple EEG Data Domains with Adversarial Learning
David Bethge, Philipp Hallgarten, Ozan Özdenizci +3
Electroencephalography (EEG) is shown to be a valuable data source for evaluating subjects' mental states. However, the interpretation of multi-modal EEG signals is challenging, as…
Universal Physiological Representation Learning with Soft-Disentangled Rateless Autoencoders
Mo Han, Ozan Ozdenizci, Toshiaki Koike-Akino +2
Human computer interaction (HCI) involves a multidisciplinary fusion of technologies, through which the control of external devices could be achieved by monitoring physiological st…
Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction
Mo Han, Ozan Ozdenizci, Ye Wang +2
Recent developments in biosignal processing have enabled users to exploit their physiological status for manipulating devices in a reliable and safe manner. One major challenge of…
Disentangled Adversarial Transfer Learning for Physiological Biosignals
Mo Han, Ozan Ozdenizci, Ye Wang +2
Recent developments in wearable sensors demonstrate promising results for monitoring physiological status in effective and comfortable ways. One major challenge of physiological st…
Adversarial Feature Learning in Brain Interfacing: An Experimental Study on Eliminating Drowsiness Effects
Ozan Ozdenizci, Barry Oken, Tab Memmott +2
Across- and within-recording variabilities in electroencephalographic (EEG) activity is a major limitation in EEG-based brain-computer interfaces (BCIs). Specifically, gradual chan…
Neural Signatures of Motor Skill in the Resting Brain
Ozan Özdenizci, Timm Meyer, Felix Wichmann +4
Stroke-induced disturbances of large-scale cortical networks are known to be associated with the extent of motor deficits. We argue that identifying brain networks representative o…
Information Theoretic Feature Transformation Learning for Brain Interfaces
Ozan Ozdenizci, Deniz Erdogmus
Objective: A variety of pattern analysis techniques for model training in brain interfaces exploit neural feature dimensionality reduction based on feature ranking and selection he…
Adversarial Deep Learning in EEG Biometrics
Ozan Ozdenizci, Ye Wang, Toshiaki Koike-Akino +1
Deep learning methods for person identification based on electroencephalographic (EEG) brain activity encounters the problem of exploiting the temporally correlated structures or r…
Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders
Ozan Ozdenizci, Ye Wang, Toshiaki Koike-Akino +1
We introduce adversarial neural networks for representation learning as a novel approach to transfer learning in brain-computer interfaces (BCIs). The proposed approach aims to lea…
Time-Series Prediction of Proximal Aggression Onset in Minimally-Verbal Youth with Autism Spectrum Disorder Using Physiological Biosignals
Ozan Ozdenizci, Catalina Cumpanasoiu, Carla Mazefsky +4
It has been suggested that changes in physiological arousal precede potentially dangerous aggressive behavior in youth with autism spectrum disorder (ASD) who are minimally verbal…
Hierarchical Graphical Models for Context-Aware Hybrid Brain-Machine Interfaces
Ozan Ozdenizci, Sezen Yagmur Gunay, Fernando Quivira +1
We present a novel hierarchical graphical model based context-aware hybrid brain-machine interface (hBMI) using probabilistic fusion of electroencephalographic (EEG) and electromyo…