Results 51 to 60 of about 215,845 (322)
Monte Carlo Simulation of SDEs using GANs [PDF]
arXiv, 2021 Generative adversarial networks (GANs) have shown promising results when applied on partial differential equations and financial time series generation. We investigate if GANs can also be used to approximate one-dimensional Ito stochastic differential equations (SDEs). We propose a scheme that approximates the path-wise conditional distribution of SDEs
arxiv
Fictitious GAN: Training GANs with Historical Models [PDF]
, 2018 Generative adversarial networks (GANs) are powerful tools for learning generative models. In practice, the training may suffer from lack of convergence. GANs are commonly viewed as a two-player zero-sum game between two neural networks. Here, we leverage this game theoretic view to study the convergence behavior of the training process. Inspired by the
Ying Wu +4 more
openaire +3 more sources
Applied Sciences, 2019 We compared the efficiency droop of InGaN multiple-quantum-well (MQW) blue light-emitting diode (LED) structures grown on silicon(111) and c-plane sapphire substrates and analyzed the efficiency droop characteristics using the rate equation model with ...
Han-Youl Ryu +2 more
doaj +1 more source
Optics Express, 2013 The errata consists of the correction to one typo of the reach-through breakdown voltage for each p-GaN/n-GaN/p-GaN junction [Opt. Express 21, 4958-4969 (2013)].
Zhang, Zi-Hui +9 more
openaire +3 more sources
Low resistance GaN/InGaN/GaN tunnel junctions [PDF]
Applied Physics Letters, 2013 Enhanced interband tunnel injection of holes into a p-n junction is demonstrated using p-GaN/InGaN/n-GaN tunnel junctions with a specific resistivity of 1.2 × 10−4 Ω cm2. The design methodology and low-temperature characteristic of these tunnel junctions are discussed, and insertion into a p-n junction device is described.
Rajan, Siddharth +3 more
openaire +5 more sources
FEBS Open Bio, EarlyView.This review highlights how foundation models enhance predictive healthcare by integrating advanced digital twin modeling with multiomics and biomedical data. This approach supports disease management, risk assessment, and personalized medicine, with the goal of optimizing health outcomes through adaptive, interpretable digital simulations, accessible ...
Sakhaa Alsaedi +2 more
wiley +1 more source
arXiv, 2021 GAN inversion aims to invert a given image back into the latent space of a pretrained GAN model, for the image to be faithfully reconstructed from the inverted code by the generator. As an emerging technique to bridge the real and fake image domains, GAN inversion plays an essential role in enabling the pretrained GAN models such as StyleGAN and BigGAN
arxiv
A review of artificial intelligence in brachytherapy
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine learning and deep learning, in various aspects of brachytherapy.
Jingchu Chen +4 more
wiley +1 more source
UAV-Based Structural Damage Mapping: A Review
ISPRS International Journal of Geo-Information, 2019 Structural disaster damage detection and characterization is one of the oldest remote sensing challenges, and the utility of virtually every type of active and passive sensor deployed on various air- and spaceborne platforms has been assessed.
Norman Kerle +4 more
doaj +1 more source
Towards Discovery and Attribution of Open-world GAN Generated Images [PDF]
arXiv, 2021 With the recent progress in Generative Adversarial Networks (GANs), it is imperative for media and visual forensics to develop detectors which can identify and attribute images to the model generating them. Existing works have shown to attribute images to their corresponding GAN sources with high accuracy.
arxiv