Results 161 to 170 of about 5,698,498 (295)

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Speech Emotion Recognition Based on Temporal-Spatial Learnable Graph Convolutional Neural Network

The Graph Convolutional Neural Networks (GCN) method has shown excellent performance in the field of deep learning, and using graphs to represent speech data is a computationally efficient and scalable approach.
Ying Liu, Jingjie Yan, Fengfeng Xu, Yuan Yang, Xiaoyang Zhou, Haihua Li   +5 more
core   +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

A low-cost neural sorting network with O(1) time complexity [PDF]

, 2011
[[abstract]]In this paper, we present an O(1) time neural network with O(n1 + var epsilon) neurons and links to sort n data, var epsilon > 0. For large-size problems, it is desirable to have low-cost hardware solutions.
Lin, Shun-Shii;Hsu, Shen-Hsuan
core  

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

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

Complexity-based graph convolutional neural network for epilepsy diagnosis in normal, acute, and chronic stages. [PDF]

Front Comput Neurosci, 2023
Zheng S, Zhang X, Song P, Hu Y, Gong X, Peng X.   +5 more
europepmc   +1 more source

Epilepsy Detection Based on Graph Convolutional Neural Network and Transformer

Epilepsy detection is a critical medical task, but traditional methods face challenges in accuracy and reliability due to the difficulty of EEG data acquisition and the limitation of the number of sample seizures. To overcome these challenges, this paper
Shibo Nie
core   +1 more source

Advancing Efficient Error Reduction in DNA Data Storage Systems with Deep Learning‐Based Denoising Models

Advanced Intelligent Discovery, EarlyView.
Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo, Anshula Tandon, Nguyen Kim Uyen, Quoc Nam Le, Jee‐Hyong Lee, Sung Ha Park   +5 more
wiley   +1 more source

Heterogeneous Graph Convolutional Neural Network via Hodge-Laplacian for Brain Functional Data. [PDF]

Inf Process Med Imaging, 2023
Huang J, Chung MK, Qiu A.
europepmc   +1 more source