Results 111 to 120 of about 37,604 (258)

Application of Graph Convolutional Neural Networks Combined with Single-Model Decision-Making Fusion Neural Networks in Structural Damage Recognition. [PDF]

Sensors (Basel), 2023
Li X, Xu L, Guo H, Yang L.
europepmc   +1 more source

Synergistic Integration of Artificial Merkel Disc and Meissner Corpuscle via Dermal Papillary Structures for Mechanically Filtered Multimodal Tactile Sensing

Advanced Science, EarlyView.
A multimodal tactile sensor module that mimics the spatial arrangement and function of Merkel discs and Meissner corpuscles within the human papillary structure operates in a self‐powered manner, responding to both dynamic and static stimuli, achieving tactile perception more similar to human skin.
Jaehyeong Kim, Bohee Maeng, Seunghwan Seo, Kyoung‐Yong Chun, Chang‐Soo Han   +4 more
wiley   +1 more source

DeepBindGCN: Integrating Molecular Vector Representation with Graph Convolutional Neural Networks for Protein-Ligand Interaction Prediction. [PDF]

Molecules, 2023
Zhang H, Saravanan KM, Zhang JZH.
europepmc   +1 more source

Graph Neural Networks Exploration

, 2023
Táto práca sa venuje rozboru metód grafových neurónových sietí pre klasifikáciu vrcholov a grafov. Skúma súčasné knižnice na prácu s grafovými neurónovými sieťami ako StellarGraph, PyTorch Geometric a DGL.
Barbara Bobeničová
core  

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, Xia Ling, Xianhe Zhang, Chuanjiang Jian, Leilei Shi, Wentao Song, Xiaonan Wang, Bin Liu   +7 more
wiley   +1 more source

Super High-Throughput Screening of Enzyme Variants by Spectral Graph Convolutional Neural Networks. [PDF]

J Chem Theory Comput, 2023
Ramírez-Palacios C, Marrink SJ.
europepmc   +1 more source

What Do Graph Convolutional Neural Networks Learn?

, 2022
Graph neural networks (GNNs) have gained traction over the past few years for their superior performance in numerous machine learning tasks. Graph Convolutional Neural Networks (GCN) are a common variant of GNNs that are known to have high performance in
Bhasin, Sannat Singh, Sanjanwala, Divij, Holani, Vaibhav   +2 more
core  

Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates

Advanced Science, EarlyView.
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao, Yufei Liu, Ruixi Huang, Zhongxue Gan, Siyang Leng   +4 more
wiley   +1 more source

Advancing the Design of High‐Efficiency Printable Hole‐Conductor‐Free Mesoscopic Perovskite Solar Cells Through Machine Learning

Advanced Science, EarlyView.
Based on the largest printable mesoscopic perovskite solar cells database we established, stacking model achieved precise PCE prediction (R2 = 0.73, MAE = 2.18%). Multiple experiments verified the accuracy of the model, which guided the fabrication of high‐PCE devices with an efficiency of 19.36%.
Hao Meng, Jingzi Zhang, Xu Zhu, Yuelin Wang, Antai Yang, Kailong Hu, Chengquan Zhong, Jiakai Liu, Menghan Dun, Xi Lin   +9 more
wiley   +1 more source

NeurstrucEnergy: A bi-directional GNN model for energy prediction of neural networks in IoT

Digital Communications and Networks
A significant demand rises for energy-efficient deep neural networks to support power-limited embedding devices with successful deep learning applications in IoT and edge computing fields.
Chaopeng Guo, Zhaojin Zhong, Zexin Zhang, Jie Song   +3 more
doaj   +1 more source