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Подтверждение методом картирования тока, наведенного электронным пучком, самопроизвольного легирования GaN нитевидных нанокристаллов из вицинальной подложки SiC/Si

Конденсированные среды и межфазные границы, 2023
Данная работа посвящена подтверждению спонтанного легирования GaN нитевидных нанокристаллов, выращенных на вицинальных гибридных подложках SiC/Si, методом картирования тока, наведенного электронным пучком.
Родион Романович Резник, Владислав Олегович Гридчин, Константин Павлович Котляр, Владимир Владимирович Неплох, Андрей Викторович Осипов, Сергей Арсеньевич Кукушкин, Omar Saket, Maria Tchernycheva, Георгий Эрнстович Цырлин   +8 more
doaj   +1 more source

The Numerics of GANs

CoRR, 2017
In this paper, we analyze the numerics of common algorithms for training Generative Adversarial Networks (GANs). Using the formalism of smooth two-player games we analyze the associated gradient vector field of GAN training objectives. Our findings suggest that the convergence of current algorithms suffers due to two factors: i) presence of eigenvalues
Mescheder, L., Nowozin, S., Geiger, A.
openaire   +4 more sources

Prb-GAN: A Probabilistic Framework for GAN Modelling

CoRR, 2021
Generative adversarial networks (GANs) are very popular to generate realistic images, but they often suffer from the training instability issues and the phenomenon of mode loss. In order to attain greater diversity in GAN synthesized data, it is critical to solving the problem of mode loss.
Blessen George, Vinod K. Kurmi, Vinay P. Namboodiri   +2 more
openaire   +2 more sources

The GAN is dead; long live the GAN! A Modern GAN Baseline

Advances in Neural Information Processing Systems 37
There is a widely-spread claim that GANs are difficult to train, and GAN architectures in the literature are littered with empirical tricks. We provide evidence against this claim and build a modern GAN baseline in a more principled manner. First, we derive a well-behaved regularized relativistic GAN loss that addresses issues of mode dropping and non ...
Nick Huang, Aaron Gokaslan, Volodymyr Kuleshov, James Tompkin 0001   +3 more
openaire   +3 more sources

Federated split GANs

Proceedings of the 1st ACM Workshop on Data Privacy and Federated Learning Technologies for Mobile Edge Network, 2022
Mobile devices and the immense amount and variety of data they generate are key enablers of machine learning (ML)-based applications. Traditional ML techniques have shifted toward new paradigms such as federated (FL) and split learning (SL) to improve the protection of user's data privacy. However, these paradigms often rely on server(s) located in the
Pranvera Kortoçi, Yilei Liang, Pengyuan Zhou, Lik-Hang Lee, Abbas Mehrabi, Pan Hui 0001, Sasu Tarkoma, Jon Crowcroft   +7 more
openaire   +2 more sources

Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig, Nadav Amir, Maya Schiller, Roni Loebenstein, Johnatan Nissan, Marina Boxer, Shany Guly Gofrit, Gal Goshen, Sándor Beniczky, Nicola Maggio   +9 more
wiley   +1 more source

Wasserstein GAN

CoRR, 2017
We introduce a new algorithm named WGAN, an alternative to traditional GAN training. In this new model, we show that we can improve the stability of learning, get rid of problems like mode collapse, and provide meaningful learning curves useful for debugging and hyperparameter searches.
Martín Arjovsky, Soumith Chintala, Léon Bottou   +2 more
openaire   +2 more sources

Coincident electron channeling and cathodoluminescence studies of threading dislocations in GaN

, 2014
We combine two scanning electron microscopy techniques to investigate the influence of dislocations on the light emission from nitride semiconductors.
Edwards, P. R., Bruckbauer, J., Oliver, R. A., Kraeusel, S., Moram, M. A., Lovelock, S., Trager-Cowan, C., Naresh-Kumar, G., Martin, R. W., Humphreys, C. J., Hourahine, B., Kappers, M. J.   +11 more
core   +1 more source

Workflow for Design of Experiments‐Based Modeling of Species Transport and Growth Kinetics in GaN Hydride Vapor Phase Epitaxy

Advanced Engineering Materials, EarlyView.
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič, G. Lukin, H. Torkashvand, A. Kerschbaum, M. Müller, S. Besendörfer, J. Heitmann, J. Friedrich   +7 more
wiley   +1 more source

Adaptive Contrast Enhancement for Digital Radiographic Images using Image-to-Image Translation

Current Directions in Biomedical Engineering
Digital radiography in medicine is a widely used imaging method for obtaining visual information about the inside of a body. To prepare the acquired raw image for diagnostic evaluation, the contrast must be adjusted depending on the examined part of the ...
Popp Ann-Kathrin, Schumacher Mona, Himstedt Marian   +2 more
doaj   +1 more source