Results 191 to 200 of about 3,278,052 (298)

Spatio-temporal graph convolutional networks with transfer learning for continuous ground reaction force estimation in hemiparetic gait. [PDF]

Front Bioeng Biotechnol
Meng Q, Yang Z, Xue Y, Zhou L, Zhang N, Xiao M, Feng X, Bao C.   +7 more
europepmc   +1 more source

Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction

Advanced Intelligent Discovery, EarlyView.
Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong, Lejia Wang, Tianqing Zhu, Keith Butler, Sichao Li   +4 more
wiley   +1 more source

Graph convolutional networks for inferring cell-cell communication from spatial transcriptomics data. [PDF]

Bioinform Adv
Kouznetsov R, Loper J, Regier J.
europepmc   +1 more source

Materials Representation Learning Based on a Material–Motif Network and Heterogeneous Graphs

Advanced Intelligent Discovery, EarlyView.
Structure motifs in materials are used to construct a bipartite material–motif network that links each material to its constituent motifs and establishes connectivity among materials sharing common motifs. Network analysis reveals material clusters associated with different functional applications and supports motif‐guided screening of materials.
Anoj Aryal, Weiyi Gong, Huta Banjade, Qimin Yan   +3 more
wiley   +1 more source

Hybrid vision-IMU deep learning framework with graph convolutional networks and attention for personalized yoga posture identification. [PDF]

Sci Rep
Vallabhaneni N, Panneer P.
europepmc   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Causal inference-integrated temporal graph convolutional networks for dynamic prediction and optimization of enterprise total factor productivity. [PDF]

Sci Rep
Fu G.
europepmc   +1 more source

Catalyst‐Specialized Chemical Language Model Based on Transformer Variational Autoencoder for Catalyst Design and Discovery

Advanced Intelligent Discovery, EarlyView.
We present CatTransVAE, a catalyst‐specialized chemical language model (CLM) built on a transformer variational autoencoder (VAE), developed through pretraining on general compounds followed by fine‐tuning on diverse catalyst databases. A template‐guided generation framework is introduced to enable controlled catalyst design under structural ...
Apakorn Kengkanna, Masahito Ohue
wiley   +1 more source

Automated Diagnosis of Hypertensive Retinopathy Using Res-UNet and Graph Convolutional Networks. [PDF]

Healthc Technol Lett
Al Sariera EMJ.
europepmc   +1 more source

Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation

Advanced Intelligent Discovery, EarlyView.
Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei, Sadman Sadeed Omee, Rongzhi Dong, Nihang Fu, Yuqi Song, Edirisuriya M. Dilanga Siriwardane, Meiling Xu, Ming Hu, Chris Wolverton, Jianjun Hu   +9 more
wiley   +1 more source