Results 71 to 80 of about 409,466 (266)

Graph neural networks for materials science and chemistry

Communications Materials, 2022
Graph neural networks are machine learning models that directly access the structural representation of molecules and materials. This Review discusses state-of-the-art architectures and applications of graph neural networks in materials science and ...
Patrick Reiser, Marlen Neubert, André Eberhard, Luca Torresi, Chen Zhou, Chen Shao, Houssam Metni, Clint van Hoesel, Henrik Schopmans, Timo Sommer, Pascal Friederich   +10 more
doaj   +1 more source

Scalable algorithms for physics-informed neural and graph networks

Data-Centric Engineering, 2022
Physics-informed machine learning (PIML) has emerged as a promising new approach for simulating complex physical and biological systems that are governed by complex multiscale processes for which some data are also available.
Khemraj Shukla, Mengjia Xu, Nathaniel Trask, George E. Karniadakis   +3 more
doaj   +1 more source

Age‐Related Characteristics of SYT1‐Associated Neurodevelopmental Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives We describe the clinical manifestations and developmental abilities of individuals with SYT1‐associated neurodevelopmental disorder (Baker‐Gordon syndrome) from infancy to adulthood. We further describe the neuroradiological and electrophysiological characteristics of the condition at different ages, and explore the associations ...
Sam G. Norwitz, Josefine Eck, Joel S. Winston, Kate Baker   +3 more
wiley   +1 more source

Deep learning-based spatial-temporal graph neural networks for price movement classification in crude oil and precious metal markets

Machine Learning with Applications
In this study, we adapt three spatial-temporal graph neural network models to the unique characteristics of crude oil, gold, and silver markets for forecasting purposes.
Parisa Foroutan, Salim Lahmiri
doaj   +1 more source

Functional Connectivity Linked to Cognitive Recovery After Minor Stroke

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Patients with minor stroke exhibit slowed processing speed and generalized alterations in functional connectivity involving frontoparietal cortex (FPC). The pattern of connectivity evolves over time. In this study, we examine the relationship of functional connectivity patterns to cognitive performance, to determine ...
Vrishab Commuri, Isabella Dallasta, Ciaran Stone, Sophia Girgenti, Neda Gould, Rafael H. Llinas, Jonathan Z. Simon, Elisabeth Breese Marsh   +7 more
wiley   +1 more source

Graph Neural Networks for Graph Drawing

IEEE Transactions on Neural Networks and Learning Systems
Accepted for publication in IEEE Transaction of Neural Networks and Learning Systems (TNNLS) 2022, Special Issue on Deep Neural Networks for Graphs: Theory, Models, Algorithms and ...
Matteo Tiezzi, Gabriele Ciravegna, Marco Gori   +2 more
openaire   +7 more sources

AAGCN: a graph convolutional neural network with adaptive feature and topology learning

Scientific Reports
In recent years, there has been a growing prevalence of deep learning in various domains, owing to advancements in information technology and computing power.
Bin Wang, Bodong Cai, Jinfang Sheng, Wenzhe Jiao   +3 more
doaj   +1 more source

Diffusion Spectrum Imaging Maps Early Axonal Loss and a Unique Progressive Signal in Neuronal Intranuclear Inclusion Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To delineate specific in vivo white matter pathology in neuronal intranuclear inclusion disease (NIID) using diffusion spectrum imaging (DSI) and define its clinical relevance. Methods DSI was performed on 42 NIID patients and 38 matched controls.
Kaiyan Jiang, Yixiu Pei, Xiaobao Hu, Ying Xiong, Fang Wang, Yanyan Yu, Min Zhu, Dandan Tan, Meihong Zhou, Daojun Hong, Fuqing Zhou   +10 more
wiley   +1 more source

Structure–Function Decoupling of the Sensorimotor and Default Mode Networks in Black Americans With MS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Multiple sclerosis (MS) exhibits racially disparate rates of disease progression. Black people with MS (B‐PwMS) experience a more severe disease course than non‐Hispanic White people with MS (NHW‐PwMS). Here we investigated structural and functional connectivity as well as structure–function decoupling in the ...
Emilio Cipriano, Giacomo Boffa, Maria Petracca, Marta Ponzano, Nicole Graziano, Claire Wigley, Claire Riley, Jonathan Howard, Pietro Bontempi, Sylvia Klineova, Fred Lublin, Matilde Inglese   +11 more
wiley   +1 more source

Thermodynamics-consistent graph neural networks

Chemical Science
We propose excess Gibbs free energy graph neural networks (GE-GNNs) for predicting composition-dependent activity coefficients of binary mixtures.
Rittig, Jan Gerald, Mitsos, Alexander
openaire   +5 more sources