Results 81 to 90 of about 221,929 (334)

Learning Crystallographic Disorder: Bridging Prediction and Experiment in Materials Discovery

Advanced Materials, EarlyView.
Machine learning based computational materials discovery workflows have recently proposed thousands of potentially stable crystalline materials. However, the experimental realization of these predictions is often challenging because the models assume perfectly ordered structures.
Konstantin S. Jakob, Aron Walsh, Karsten Reuter, Johannes T. Margraf   +3 more
wiley   +1 more source

GAGAN: Geometry-Aware Generative Adversarial Networks

, 2018
Deep generative models learned through adversarial training have become increasingly popular for their ability to generate naturalistic image textures.
Kossaifi, Jean, Panagakis, Yannis, Pantic, Maja, Tran, Linh   +3 more
core   +1 more source

GANE: A Generative Adversarial Network Embedding [PDF]

IEEE Transactions on Neural Networks and Learning Systems, 2019
Network embedding has become a hot research topic recently which can provide low-dimensional feature representations for many machine learning applications. Current work focuses on either (1) whether the embedding is designed as an unsupervised learning task by explicitly preserving the structural connectivity in the network, or (2) whether the ...
Huiting Hong, Xin Li, Mingzhong Wang
openaire   +4 more sources

Active Learning‐Guided Accelerated Discovery of Ultra‐Efficient High‐Entropy Thermoelectrics

Advanced Materials, EarlyView.
An active learning framework is introduced for the accelerated discovery of high‐entropy chalcogenides with superior thermoelectric performance. Only 80 targeted syntheses, selected from 16206 possible combinations, led to three high‐performance compositions, demonstrating the remarkable efficiency of data‐driven guidance in experimental materials ...
Hanhwi Jang, Wooseok Lee, Hwa‐Jung Kim, Sohyang Cha, Hosun Shin, Won Bo Lee, Min‐Wook Oh, Yeon Sik Jung, YongJoo Kim   +8 more
wiley   +1 more source

A Review of the Research and Development of Adversarial Generative Networks in Interior Graphic Design [PDF]

ITM Web of Conferences
This study provides a comprehensive overview of the research and development of adversarial generative networks in interior graphic design. With the continuous development of adversarial generative networks, the level of Generative Adversarial Networks ...
Yang Haonan
doaj   +1 more source

A survey on text generation using generative adversarial networks [PDF]

, 2021
Gustavo Henrique de Rosa, João Paulo Papa   +1 more
openalex   +1 more source

DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction

IEEE Transactions on Medical Imaging, 2018
Compressed sensing magnetic resonance imaging (CS-MRI) enables fast acquisition, which is highly desirable for numerous clinical applications. This can not only reduce the scanning cost and ease patient burden, but also potentially reduce motion ...
Guang Yang, Simiao Yu, Hao Dong, G. Slabaugh, P. Dragotti, Xujiong Ye, Fangde Liu, S. Arridge, J. Keegan, Yike Guo, D. Firmin   +10 more
semanticscholar   +1 more source

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

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, Yaroslav Mudryk, Jun Cui, Lucas Griffith, Duane D. Johnson, Julie Slaughter   +5 more
wiley   +1 more source

Multiparameter Closed‐Loop Control to Advance Reliability of Aerosol Jet Printing

Advanced Materials Technologies, EarlyView.
A multiparameter framework for closed‐loop control of aerosol jet printing is developed to improve process consistency over both short and long timescales. By creating a control architecture responsive to the dynamic behavior of the printing system, variability in functional electrical properties is significantly reduced over extended duration printing,
Andrew J. Schwartz, Jeremy D. Rurup, Ethan B. Secor   +2 more
wiley   +1 more source

A Social Recommendation Model Based on Basic Spatial Mapping and Bilateral Generative Adversarial Networks

Entropy, 2023
Social recommender systems are expected to improve recommendation quality by incorporating social information when there is little user–item interaction data. Therefore, how to effectively fuse interaction information and social information becomes a hot
Suqi Zhang, Ningjing Zhang, Wenfeng Wang, Qiqi Liu, Jianxin Li   +4 more
doaj   +1 more source