Results 61 to 70 of about 39,632 (294)
Graphical Generative Adversarial Networks
CoRR, 2018 We propose Graphical Generative Adversarial Networks (Graphical-GAN) to model structured data. Graphical-GAN conjoins the power of Bayesian networks on compactly representing the dependency structures among random variables and that of generative adversarial networks on learning expressive dependency functions.
Chongxuan Li +3 more
openaire +3 more sources
Robust Generative Adversarial Network
CoRR, 2020 Generative adversarial networks (GANs) are powerful generative models, but usually suffer from instability and generalization problem which may lead to poor generations. Most existing works focus on stabilizing the training of the discriminator while ignoring the generalization properties.
Shufei Zhang +4 more
openaire +2 more sources
3D Printing Innovations in Polymeric Porous and Patterned Architecture
Advanced Functional Materials, EarlyView.Polymeric foams occupy a unique structural space between dense solids and open networks, where engineered void fraction governs mechanical compliance, thermal resistance, and mass transport. Additive manufacturing now enables precise spatial control over cellular architecture, unlocking designer foam structures across applications spanning crash ...
Dhanush Patil +13 more
wiley +1 more source
, 2021 Microkinetic analysis based on density functional theory (DFT) was combined with a generative adversarial network (GAN) to enable artificial proposal of heterogeneous catalysts based on the DFT-calculated dataset.
Atsushi, Ishikawa
core +1 more source
Coupled Generative Adversarial Networks
CoRR, 2016 We propose coupled generative adversarial network (CoGAN) for learning a joint distribution of multi-domain images. In contrast to the existing approaches, which require tuples of corresponding images in different domains in the training set, CoGAN can learn a joint distribution without any tuple of corresponding images.
Ming-Yu Liu 0001, Oncel Tuzel
openaire +3 more sources
Advanced Materials, EarlyView.This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley +1 more source
Deep learning generative adversarial network model for automated detection of diabetic retinopathy [PDF]
Diabetic retinopathy (DR) is a leading disease that cause impaired vision with a consequence of permanent blindness if it is undiagnosed and untreated at the early stages. Alas, DR often has no early warning sign and may cause no symptoms.
Shafie, Muhammad Laziem +4 more
core +1 more source
Progressive growing of generative adversarial network (GAN) (PGGAN) training.
, 2020 Progressive growing of generative adversarial network (GAN) (PGGAN) training.
Kazuyoshi Imaizumi (488891) +6 more
core +1 more source
Inverse Design of Amorphous Materials With Targeted Properties
Advanced Materials, EarlyView.AMDEN is a diffusion model framework for the inverse design of amorphous materials with targeted properties. By incorporating Hamiltonian Monte Carlo refinement into the denoising process, the framework overcomes the challenge of generating thermally relaxed disordered structures.
Jonas A. Finkler +4 more
wiley +1 more source
Survey of generative adversarial network
网络与信息安全学报, 2021 Firstly, the basic theory, application scenarios and current state of research of GAN (generative adversarial network) were introduced, and the problems need to be improved were listed. Then, recent research, improvement mechanism and model features in 2
WANG Zhenglong, ZHANG Baowen
doaj +1 more source