Zobrazeno 1 - 10
of 57 393
pro vyhledávání: '"and, Yunus"'
Autor:
Celik, Mehmet, Duguin, Mathis, Guo, Jia, Luo, Dianlun, Spinelli, Kamryn, Zeytuncu, Yunus E., Zhu, Zhuoyu
In 2021, Dan Reznik made a YouTube video demonstrating that power circles of Poncelet triangles have an invariant total area. He made a simulation based on this observation and put forward a few conjectures. One of these conjectures suggests that the
Externí odkaz:
http://arxiv.org/abs/2410.18863
Autor:
Yuan, Yuncheng, Scheepers, Péter, Tasiou, Lydia, Gültekin, Yunus Can, Corradi, Federico, Alvarado, Alex
This paper analyzes the design and competitiveness of four neural network (NN) architectures recently proposed as decoders for forward error correction (FEC) codes. We first consider the so-called single-label neural network (SLNN) and the multi-labe
Externí odkaz:
http://arxiv.org/abs/2410.15899
Autor:
Yunus, Fajrian, Abdessalem, Talel
A lot of effort in recent years have been expended to explain machine learning systems. However, some machine learning methods are inherently explainable, and thus are not completely black box. This enables the developers to make sense of the output
Externí odkaz:
http://arxiv.org/abs/2410.03841
Autor:
Kartal, Enise, Selcuk, Yunus, Kaynak, Batuhan E., Yildiz, M. Taha, Yanik, Cenk, Hanay, M. Selim
Reservoir computing offers an energy-efficient alternative to deep neural networks (DNNs) by replacing complex hidden layers with a fixed nonlinear system and training only the final layer. This work investigates nanoelectromechanical system (NEMS) r
Externí odkaz:
http://arxiv.org/abs/2409.16805
Autor:
Gümüş, Kadir, Frazão, João dos Reis, Albores-Mejia, Aaron, Škorić, Boris, Liga, Gabriele, Gültekin, Yunus Can, Bradley, Thomas, Alvarado, Alex, Okonkwo, Chigo
In this paper we introduce a reconciliation protocol with a two-step error correction scheme using a short blocklength low rate code and a long blocklength high rate code. We show that by using this two-step decoding method it is possible to achieve
Externí odkaz:
http://arxiv.org/abs/2409.13667
In recent years, transformer-based architectures become the de facto standard for sequence modeling in deep learning frameworks. Inspired by the successful examples, we propose a causal visual-inertial fusion transformer (VIFT) for pose estimation in
Externí odkaz:
http://arxiv.org/abs/2409.08769
Finding optimal policies for Partially Observable Markov Decision Processes (POMDPs) is challenging due to their uncountable state spaces when transformed into fully observable Markov Decision Processes (MDPs) using belief states. Traditional methods
Externí odkaz:
http://arxiv.org/abs/2409.04351
Skin cancer segmentation poses a significant challenge in medical image analysis. Numerous existing solutions, predominantly CNN-based, face issues related to a lack of global contextual understanding. Alternatively, some approaches resort to large-s
Externí odkaz:
http://arxiv.org/abs/2409.03062
Autor:
Yunus, Sameen, Strubbe, David A.
Accurate modeling in the warm dense matter regime is a persistent challenge with the most detailed models such as quantum molecular dynamics and path integral Monte Carlo being immensely computationally expensive. Density functional theory (DFT)-base
Externí odkaz:
http://arxiv.org/abs/2409.02105
We introduce Spurfies, a novel method for sparse-view surface reconstruction that disentangles appearance and geometry information to utilize local geometry priors trained on synthetic data. Recent research heavily focuses on 3D reconstruction using
Externí odkaz:
http://arxiv.org/abs/2408.16544