Large-scale dark matter simulations
We review the field of collisionless numerical simulations for the large-scale structure of the
Universe. We start by providing the main set of equations solved by these simulations and …
Universe. We start by providing the main set of equations solved by these simulations and …
Recent progress in transformer-based medical image analysis
The transformer is primarily used in the field of natural language processing. Recently, it has
been adopted and shows promise in the computer vision (CV) field. Medical image analysis …
been adopted and shows promise in the computer vision (CV) field. Medical image analysis …
Generative adversarial networks for data augmentation in machine fault diagnosis
Generative adversarial networks (GANs) have been proved to be able to produce artificial
data that are alike the real data, and have been successfully applied to various image …
data that are alike the real data, and have been successfully applied to various image …
On the regularization of wasserstein gans
Since their invention, generative adversarial networks (GANs) have become a popular
approach for learning to model a distribution of real (unlabeled) data. Convergence …
approach for learning to model a distribution of real (unlabeled) data. Convergence …
Density estimation using deep generative neural networks
Density estimation is one of the fundamental problems in both statistics and machine
learning. In this study, we propose Roundtrip, a computational framework for general …
learning. In this study, we propose Roundtrip, a computational framework for general …
Building layout generation using site-embedded GAN model
Building layout generation has entered a new era in recent years, leveraging state-of-the-art
deep generative methods to learn morphological properties of exiting urban structures and …
deep generative methods to learn morphological properties of exiting urban structures and …
Controlling generative models with continuous factors of variations
Recent deep generative models are able to provide photo-realistic images as well as visual
or textual content embeddings useful to address various tasks of computer vision and …
or textual content embeddings useful to address various tasks of computer vision and …
Stochastic reconstruction of an oolitic limestone by generative adversarial networks
Stochastic image reconstruction is a key part of modern digital rock physics and material
analysis that aims to create representative samples of microstructures for upsampling …
analysis that aims to create representative samples of microstructures for upsampling …
Event generation and statistical sampling for physics with deep generative models and a density information buffer
Simulating nature and in particular processes in particle physics require expensive
computations and sometimes would take much longer than scientists can afford. Here, we …
computations and sometimes would take much longer than scientists can afford. Here, we …
A GAN-based model of deepfake detection in social media
Abstract DeepFake uses Generative+ Adversarial Network for successfully switching the
identities of two people. Large public databases and deep learning methods are now rapidly …
identities of two people. Large public databases and deep learning methods are now rapidly …