Deniz Erdogmus

NetCut: Real-Time DNN Inference Using Layer Removal

Deep Learning plays a significant role in assisting humans in many aspec...
01/13/2021 ∙ by Mehrshad Zandigohar, et al. ∙ 0 ∙ share

read it
Towards Creating a Deployable Grasp Type Probability Estimator for a Prosthetic Hand

For lower arm amputees, prosthetic hands promise to restore most of phys...
01/13/2021 ∙ by Mehrshad Zandigohar, et al. ∙ 0 ∙ share

read it
Universal Physiological Representation Learning with Soft-Disentangled Rateless Autoencoders

Human computer interaction (HCI) involves a multidisciplinary fusion of ...
09/28/2020 ∙ by Mo Han, et al. ∙ 0 ∙ share

read it
Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction

Recent developments in biosignal processing have enabled users to exploi...
08/26/2020 ∙ by Mo Han, et al. ∙ 5 ∙ share

read it
Stopping Criterion Design for Recursive Bayesian Classification: Analysis and Decision Geometry

Systems that are based on recursive Bayesian updates for classification ...
07/30/2020 ∙ by Aziz Koçanaoğulları, et al. ∙ 7 ∙ share

read it
AutoBayes: Automated Inference via Bayesian Graph Exploration for Nuisance-Robust Biosignal Analysis

Learning data representations that capture task-related features, but ar...
07/02/2020 ∙ by Andac Demir, et al. ∙ 74 ∙ share

read it
Prediction of Epilepsy Development in Traumatic Brain Injury Patients from Diffusion Weighted MRI

Post-traumatic epilepsy (PTE) is a life-long complication of traumatic b...
04/30/2020 ∙ by Md Navid Akbar, et al. ∙ 0 ∙ share

read it
Disentangled Adversarial Transfer Learning for Physiological Biosignals

Recent developments in wearable sensors demonstrate promising results fo...
04/15/2020 ∙ by Mo Han, et al. ∙ 9 ∙ share

read it
Active Recursive Bayesian Inference with Posterior Trajectory Analysis Using α-Divergence

Recursive Bayesian inference (RBI) provides optimal Bayesian latent vari...
04/07/2020 ∙ by Yeganeh M. Marghi, et al. ∙ 4 ∙ share

read it
Mapping Motor Cortex Stimulation to Muscle Responses: A Deep Neural Network Modeling Approach

A deep neural network (DNN) that can reliably model muscle responses fro...
02/14/2020 ∙ by Md Navid Akbar, et al. ∙ 23 ∙ share

read it
User-Adaptive Text Entry for Augmentative and Alternative Communication

The viability of an Augmentative and Alternative Communication device of...
10/02/2019 ∙ by Matt Higger, et al. ∙ 0 ∙ share

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

Across- and within-recording variabilities in electroencephalographic (E...
07/22/2019 ∙ by Ozan Özdenizci, et al. ∙ 0 ∙ share

read it
Information Theoretic Feature Transformation Learning for Brain Interfaces

Objective: A variety of pattern analysis techniques for model training i...
03/28/2019 ∙ by Ozan Özdenizci, et al. ∙ 0 ∙ share

read it
Adversarial Deep Learning in EEG Biometrics

Deep learning methods for person identification based on electroencephal...
03/27/2019 ∙ by Ozan Özdenizci, et al. ∙ 1 ∙ share

read it
Accelerated Experimental Design for Pairwise Comparisons

Pairwise comparison labels are more informative and less variable than c...
01/18/2019 ∙ by Yuan Guo, et al. ∙ 0 ∙ share

read it
Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders

We introduce adversarial neural networks for representation learning as ...
12/17/2018 ∙ by Ozan Özdenizci, et al. ∙ 1 ∙ share

read it
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...
09/15/2018 ∙ by Ozan Özdenizci, et al. ∙ 0 ∙ share

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

We present a novel hierarchical graphical model based context-aware hybr...
09/15/2018 ∙ by Ozan Özdenizci, et al. ∙ 0 ∙ share

read it
Structured Adversarial Attack: Towards General Implementation and Better Interpretability

When generating adversarial examples to attack deep neural networks (DNN...
08/05/2018 ∙ by Kaidi Xu, et al. ∙ 16 ∙ share

read it
Invariant Representations from Adversarially Censored Autoencoders

We combine conditional variational autoencoders (VAE) with adversarial c...
05/21/2018 ∙ by Ye Wang, et al. ∙ 1 ∙ share

read it
Tversky as a Loss Function for Highly Unbalanced Image Segmentation using 3D Fully Convolutional Deep Networks

Fully convolutional deep neural networks have been asserted to be fast a...
03/28/2018 ∙ by Seyed Raein Hashemi, et al. ∙ 0 ∙ share

read it
Real-time Deep Registration With Geodesic Loss

With an aim to increase the capture range and accelerate the performance...
03/15/2018 ∙ by Seyed Sadegh Mohseni Salehi, et al. ∙ 0 ∙ share

read it
Real-Time Automatic Fetal Brain Extraction in Fetal MRI by Deep Learning

Brain segmentation is a fundamental first step in neuroimage analysis. I...
10/25/2017 ∙ by Seyed Sadegh Mohseni Salehi, et al. ∙ 0 ∙ share

read it
Tversky loss function for image segmentation using 3D fully convolutional deep networks

Fully convolutional deep neural networks carry out excellent potential f...
06/18/2017 ∙ by Seyed Sadegh Mohseni Salehi, et al. ∙ 0 ∙ share

read it
Auto-context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging

Brain extraction or whole brain segmentation is an important first step ...
03/06/2017 ∙ by Seyed Sadegh Mohseni Salehi, et al. ∙ 0 ∙ share

read it
Asymptotic Analysis of Objectives based on Fisher Information in Active Learning

Obtaining labels can be costly and time-consuming. Active learning allow...
05/27/2016 ∙ by Jamshid Sourati, et al. ∙ 0 ∙ share

read it
Manifold unwrapping using density ridges

Research on manifold learning within a density ridge estimation framewor...
04/06/2016 ∙ by Jonas Nordhaug Myhre, et al. ∙ 0 ∙ share

read it

Deniz Erdogmus

Featured Co-authors

Pin-Yu Chen

Yanzhi Wang

Sijia Liu

Xue Lin

Huan Zhang

Robert Jenssen

Ye Wang

Stratis Ioannidis

Kaidi Xu

Toshiaki Koike-Akino

Jennifer Dy

NetCut: Real-Time DNN Inference Using Layer Removal

Towards Creating a Deployable Grasp Type Probability Estimator for a Prosthetic Hand

Universal Physiological Representation Learning with Soft-Disentangled Rateless Autoencoders

Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction

Stopping Criterion Design for Recursive Bayesian Classification: Analysis and Decision Geometry

AutoBayes: Automated Inference via Bayesian Graph Exploration for Nuisance-Robust Biosignal Analysis

Prediction of Epilepsy Development in Traumatic Brain Injury Patients from Diffusion Weighted MRI

Disentangled Adversarial Transfer Learning for Physiological Biosignals

Active Recursive Bayesian Inference with Posterior Trajectory Analysis Using α-Divergence

Mapping Motor Cortex Stimulation to Muscle Responses: A Deep Neural Network Modeling Approach

User-Adaptive Text Entry for Augmentative and Alternative Communication

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

Information Theoretic Feature Transformation Learning for Brain Interfaces

Adversarial Deep Learning in EEG Biometrics

Accelerated Experimental Design for Pairwise Comparisons

Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders

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

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

Structured Adversarial Attack: Towards General Implementation and Better Interpretability

Invariant Representations from Adversarially Censored Autoencoders

Tversky as a Loss Function for Highly Unbalanced Image Segmentation using 3D Fully Convolutional Deep Networks

Real-time Deep Registration With Geodesic Loss

Real-Time Automatic Fetal Brain Extraction in Fetal MRI by Deep Learning

Tversky loss function for image segmentation using 3D fully convolutional deep networks

Auto-context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging

Asymptotic Analysis of Objectives based on Fisher Information in Active Learning

Manifold unwrapping using density ridges