Hazal Moğultay

E-mail

mogultay@metu.edu.tr

Department

Department of Computer Engineering

ORCID

0000-0002-1314-0956

Scopus Author ID

57195216706

Web of Science Researcher ID

AAZ-5721-2020

Generalized variational autoencoders for learning disentangled representation Moğultay, Hazal; KALKAN, SİNAN; Vural, Fatos T. Yarman (2025-10-14) The major goal of disentangled representation learning is to form representation space, which independently captures the underlying sources of variation, responsible for generating the data. A pioneering approach is sugges...
An Analysis on Disentanglement in Machine Learning Makine Öǧrenmesinde Ayrişiklik Üzerine Bir Analiz Moğultay, Hazal; Kalkan, Sinan; Yarman Vural, Fatoş Tunay (2022-01-01) Learnt representations by Deep autoencoders is not capable of decomposing the complex information into simple notion. In other words, attributes of samples are entangled in the basis vectors spanning the learned space. Thi...
BrainParcel: A Brain Parcellation Algorithm for Cognitive State Classification Moğultay, Hazal; Yarman Vural, Fatoş Tunay (2018-01-01) In this study, we propose a novel brain parcellation algorithm, called BrainParcel. BrainParcel defines a set of supervoxels by partitioning a voxel level brain graph into a number of subgraphs, which are assumed to repres...
Cognitive Learner: An Ensemble Learning Architecture for Cognitive State Classification Moğultay, Hazal (2017-05-18) In this study, we propose an ensemble learning architecture called "Cognitive Learner", for classification of cognitive states from functional magnetic resonance imaging (fMRI). Proposed architecture consists of a two-laye...
Classification of fMRI Data by Using Clustering Moğultay, Hazal; Yarman Vural, Fatoş Tunay (2015-05-19) Recognition of the the cognitive states by using functional Magnetic Rezonans Imaging (fMRI) data is a challenging problem that has been a focus of scientific research for a long time. In this study the effectiveness of cl...

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