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Derya Soydaner

Mimar Sinan Fine Arts University, Statistics

6 papers hereh-index 7664 citations10 works total

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

author position
  • sole author2
  • first author1
  • middle author2
  • last author1

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.CV1
  • nucl-th1
affiliations
  • Mimar Sinan Fine Arts University, Statistics
same name
  • Derya Soydaner — 11 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202023
most citedAttention Mechanism in Neural Networks: Where it Comes and Where it Goes

405 citations · 699 across the 5 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2023

From paintbrush to pixel: A review of deep neural networks in AI-generated art

Anne-Sofie Maerten, Derya Soydaner

This paper delves into the fascinating field of AI-generated art and explores the various deep neural network architectures and models that have been utilized to create it. From th…

cs.LG2022★ 17 cited

Application of multilayer perceptron with data augmentation in nuclear physics

Hüseyin Bahtiyar, Derya Soydaner, Esra Yüksel

Neural networks have become popular in many fields of science since they serve as promising, reliable and powerful tools. In this work, we study the effect of data augmentation on…

cs.LG2022★ 405 cited

Attention Mechanism in Neural Networks: Where it Comes and Where it Goes

Derya Soydaner

A long time ago in the machine learning literature, the idea of incorporating a mechanism inspired by the human visual system into neural networks was introduced. This idea is name…

cs.LG2020★ 219 cited

A Comparison of Optimization Algorithms for Deep Learning

Derya Soydaner

In recent years, we have witnessed the rise of deep learning. Deep neural networks have proved their success in many areas. However, the optimization of these networks has become m…

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