Results 81 to 90 of about 4,069,375 (260)
Broadening Hard‐Magnet Discovery Beyond Symmetry Constraints via Unified Effective Anisotropy
Advanced Science, EarlyView.A unified effective‐anisotropy descriptor (Keff) extends hard‐magnet screening across all seven crystal systems, beyond the uniaxial restriction of conventional searches. Machine‐learning screening of 9320 known ferromagnets and diffusion‐model generation together yield 38 rare‐earth‐free or ‐lean candidates with DFT‐validated magnetic hardness (κ > 1),
Hojae Kim +5 more
wiley +1 more source
Low Frequency Ultrasonic Voice Activity Detection using Convolutional Neural Networks [PDF]
Low frequency ultrasonic mouth state detection uses reflected audio chirps from the face in the region of the mouth to determine lip state, whether open, closed or partially open.
Song, Yan, McLoughlin, Ian Vince
core
Path Connectivity Based Neighbor‑Awareness Node Classification Algorithm
Shuju Caiji Yu ChuliGraph convolutional neural networks obtain the node representation by aggregating the neighbor node information with high similarity，and selecting the appropriate neighborhood for the node and conducting effective aggregation are the keys to the graph ...
ZHENG Wenping +2 more
doaj +1 more source
Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning
Transactions of the Association for Computational Linguistics, 2019 We focus on graph-to-sequence learning, which can be framed as transducing graph structures to sequences for text generation. To capture structural information associated with graphs, we investigate the problem of encoding graphs using graph ...
Guo, Zhijiang +3 more
doaj +1 more source
Scalable Graph Convolutional Networks With Fast Localized Spectral Filter for Directed Graphs
IEEE Access, 2020 Graph convolutional neural netwoks (GCNNs) have been emerged to handle graph-structured data in recent years. Most existing GCNNs are either spatial approaches working on neighborhood of each node, or spectral approaches based on graph Laplacian ...
Chensheng Li +4 more
doaj +1 more source
Advanced Science, EarlyView.A new data‐efficient framework combining DFT calculations, a neural network model, and automated graph analysis of catalytic reaction networks is proposed and applied to CO2 hydrogenation on transition metal nanoparticles. The analysis shows how efficient C2 oxygenate production requires a balance between CHx formation, C–C coupling, protonation, and ...
Mikhail V. Polynski, Sergey M. Kozlov
wiley +1 more source
Towards the Application of Backpropagation-Free Graph Convolutional Networks on Huge Datasets [PDF]
Backpropagation-Free Graph Convolutional Networks (BFGCN) are backpropagation-free neural models dealing with graph data based on Gated Linear Networks.
Nicolo Navarin +2 more
core +1 more source
Point Cloud Normal Estimation with Graph-Convolutional Neural Networks [PDF]
, 2020 Surface normal estimation is a basic task for many point cloud processing algorithms. However, it can be challenging to capture the local geometry of the data, especially in presence of noise.
Pistilli, Francesca +3 more
core +1 more source
Dual‐Module Near‐Infrared Fluorophores Discovery System via Knowledge Transfer
Advanced Science, EarlyView.This study presents a dual‐module deep learning system for the design of near‐infrared (NIR) fluorophores. A large molecular library is generated and analyzed, leading to the suggestions of promising candidates. The effectiveness of the system is further validated through the synthesis, characterization, and in vivo imaging, demonstrating its potential
Yixin Zhu +7 more
wiley +1 more source
Enhancing Super‐Resolution Spatial Transcriptomics Data by Transfer Learning
Advanced Science, EarlyView.SpotZoomer employs a transfer‐learning‐based strategy to enhance the resolution of Visium data by leveraging available high‐resolution priors. The resulting super‐resolved maps enable sharper delineation of cell boundaries and more precise inference of cell–cell communication patterns that would otherwise remain obscured at native resolution.
Xiaoyu Li, Lihua Zhang, Wenwen Min
wiley +1 more source