Results 181 to 190 of about 142,397 (310)

GCRINT: Network Traffic Imputation Using Graph Convolutional Recurrent Neural Network

, 2021
Van An Le et al.
openalex   +2 more sources

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

, 2023
Haiping Zhang, Konda Mani Saravanan, John Z.H. Zhang   +2 more
openalex   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Leveraging molecular-QTL co-association to predict novel disease-associated genetic loci using a graph convolutional neural network. [PDF]

PLoS One
Ng-Kee-Kwong J, Bretherick AD.
europepmc   +2 more sources

Improved Graph Convolutional Neural Network for Dance Tracking and Pose Estimation. [PDF]

Comput Intell Neurosci, 2022
Zhang L.
europepmc   +1 more source

FIRE‐GNN: Force‐Informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties

Advanced Intelligent Discovery, EarlyView.
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu, Claire Schlesinger, Karan Mudaliar, Jordan Leung, Robin Walters, Peter Schindler   +5 more
wiley   +1 more source

The classification of brain network for major depressive disorder patients based on deep graph convolutional neural network. [PDF]

Front Hum Neurosci, 2023
Zhu M, Quan Y, He X.
europepmc   +1 more source

Multi-Graph Convolutional Neural Network for Breast Cancer Multi-Task Classification

, 2022
Mohamed Ibrahim, Shagufta Henna, Gary Cullen, Brendan Jennings, Bernard Butler   +4 more
openalex   +1 more source

Short-term Traffic Demand Prediction using Graph Convolutional Neural Networks [PDF]

, 2020
Aoyong Li, Kay W. Axhausen
openalex   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source