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researcher

Ömer Faruk Tuna

3 papers hereh-index 247 citations2 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • eess.SP1

identity via Semantic Scholar / OpenAlex

activity
20202023
most citedExploiting epistemic uncertainty of the deep learning models to generate adversarial samples

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

eess.SP2023

Practical Adversarial Attacks Against AI-Driven Power Allocation in a Distributed MIMO Network

Ömer Faruk Tuna, Fehmi Emre Kadan, Leyli Karaçay

In distributed multiple-input multiple-output (D-MIMO) networks, power control is crucial to optimize the spectral efficiencies of users and max-min fairness (MMF) power control is…

cs.LG2021★ 1 cited

Exploiting epistemic uncertainty of the deep learning models to generate adversarial samples

Omer Faruk Tuna, Ferhat Ozgur Catak, M. Taner Eskil

Deep neural network architectures are considered to be robust to random perturbations. Nevertheless, it was shown that they could be severely vulnerable to slight but carefully cra…

cs.LG2020

Closeness and Uncertainty Aware Adversarial Examples Detection in Adversarial Machine Learning

Omer Faruk Tuna, Ferhat Ozgur Catak, M. Taner Eskil

While state-of-the-art Deep Neural Network (DNN) models are considered to be robust to random perturbations, it was shown that these architectures are highly vulnerable to delibera…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.