Ozan Özdenizci | DeepAI

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Bernhard Schölkopf
271 publications
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89 publications
Enkelejda Kasneci
49 publications
Deniz Erdogmus
48 publications
Stratis Ioannidis
40 publications
Toshiaki Koike-Akino
34 publications
Ralf Mikut
33 publications
Tonio Ball
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Albrecht Schmidt
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Moritz Grosse-Wentrup
18 publications
Sebastian Weichwald
17 publications

∙ 06/10/2023

TS-MoCo: Time-Series Momentum Contrast for Self-Supervised Physiological Representation Learning

Limited availability of labeled physiological data often prohibits the u...

0 Philipp Hallgarten, et al. ∙

∙ 07/29/2022

Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models

Image restoration under adverse weather conditions has been of significa...

6 Ozan Özdenizci, et al. ∙

∙ 07/16/2022

EEG2Vec: Learning Affective EEG Representations via Variational Autoencoders

There is a growing need for sparse representational formats of human aff...

18 David Bethge, et al. ∙

∙ 05/23/2022

Memory-enriched computation and learning in spiking neural networks through Hebbian plasticity

Memory is a key component of biological neural systems that enables the ...

0 Thomas Limbacher, et al. ∙

∙ 04/16/2022

Exploiting Multiple EEG Data Domains with Adversarial Learning

Electroencephalography (EEG) is shown to be a valuable data source for e...

17 David Bethge, et al. ∙

∙ 01/27/2022

Domain-Invariant Representation Learning from EEG with Private Encoders

Deep learning based electroencephalography (EEG) signal processing metho...

12 David Bethge, et al. ∙

∙ 05/01/2021

Stochastic Mutual Information Gradient Estimation for Dimensionality Reduction Networks

Feature ranking and selection is a widely used approach in various appli...

0 Ozan Özdenizci, et al. ∙

∙ 02/17/2021

EEG-based Texture Roughness Classification in Active Tactile Exploration with Invariant Representation Learning Networks

During daily activities, humans use their hands to grasp surrounding obj...

0 Ozan Özdenizci, et al. ∙

∙ 02/16/2021

On the use of generative deep neural networks to synthesize artificial multichannel EEG signals

Recent promises of generative deep learning lately brought interest to i...

0 Ozan Özdenizci, et al. ∙

∙ 09/28/2020

Universal Physiological Representation Learning with Soft-Disentangled Rateless Autoencoders

Human computer interaction (HCI) involves a multidisciplinary fusion of ...

0 Mo Han, et al. ∙

∙ 08/26/2020

Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction

Recent developments in biosignal processing have enabled users to exploi...

5 Mo Han, et al. ∙

∙ 04/15/2020

Disentangled Adversarial Transfer Learning for Physiological Biosignals

Recent developments in wearable sensors demonstrate promising results fo...

9 Mo Han, et al. ∙

∙ 07/22/2019

Adversarial Feature Learning in Brain Interfacing: An Experimental Study on Eliminating Drowsiness Effects

Across- and within-recording variabilities in electroencephalographic (E...

0 Ozan Özdenizci, et al. ∙

∙ 03/28/2019

Information Theoretic Feature Transformation Learning for Brain Interfaces

Objective: A variety of pattern analysis techniques for model training i...

0 Ozan Özdenizci, et al. ∙

∙ 03/27/2019

Adversarial Deep Learning in EEG Biometrics

Deep learning methods for person identification based on electroencephal...

1 Ozan Özdenizci, et al. ∙

∙ 12/17/2018

Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders

We introduce adversarial neural networks for representation learning as ...

1 Ozan Özdenizci, et al. ∙

∙ 09/15/2018

Time-Series Prediction of Proximal Aggression Onset in Minimally-Verbal Youth with Autism Spectrum Disorder Using Physiological Biosignals

It has been suggested that changes in physiological arousal precede pote...

0 Ozan Özdenizci, et al. ∙

∙ 09/15/2018

Hierarchical Graphical Models for Context-Aware Hybrid Brain-Machine Interfaces

We present a novel hierarchical graphical model based context-aware hybr...

0 Ozan Özdenizci, et al. ∙

∙ 11/15/2015

Causal interpretation rules for encoding and decoding models in neuroimaging

Causal terminology is often introduced in the interpretation of encoding...

0 Sebastian Weichwald, et al. ∙

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