Results 61 to 70 of about 4,829,196 (302)
Role of Structural Disorder on Phonon Transport and Thermal Conductivity in Li6PS5Br
Advanced Functional Materials, EarlyView.Solid electrolytes are fast ion and slow heat conductors. Although both transport properties are governed by lattice dynamics and atomic structure, their interplay remains poorly understood. Here, we study this interrelation in anion‐ordered and disordered Li6PS5Br.
Lukas Ketter +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
Facial expression transfer using generative adversarial network : a review [PDF]
, 2020 There is high demand of realistic facial expression in current computer graphics and multimedia research. Realistic and accurate facial expression can guarantee the animated character to deliver the expression correctly.
Mohd. Suaib, Norhaida +1 more
core +1 more source
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
Validating functional redundancy with mixed generative adversarial networks
, 2023 Validating functional redundancy with mixed generative adversarial ...
TT Huynh (14704033) +4 more
core
Advanced Materials, EarlyView.Self‐invalidating multilayer physical unclonable functions (PUFs) integrate fingerprint‐like metal nanopattern bilayers from block copolymer templates with highly reactive reduced graphene oxide (rGO) interlayers. This tamper‐responsive architecture blocks all unauthorized physical and chemical replication attempts while autonomously deactivating ...
Gyu Hui Jo +7 more
wiley +1 more source
MGGAN: improving sample generations of Generative Adversarial Networks
, 2022 MGGAN: improving sample generations of Generative Adversarial ...
H Wu (7724324) +5 more
core
Prescribed Generative Adversarial Networks
CoRR, 2019 Generative adversarial networks (GANs) are a powerful approach to unsupervised learning. They have achieved state-of-the-art performance in the image domain. However, GANs are limited in two ways. They often learn distributions with low support---a phenomenon known as mode collapse---and they do not guarantee the existence of a probability density ...
Adji B. Dieng +3 more
openaire +2 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 +3 more sources
Advanced Materials Technologies, EarlyView.The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz +5 more
wiley +1 more source