Results 61 to 70 of about 15,175 (257)

Bayesian reasoning for physics-informed neural networks

Physical Review E
21 pages, 12 figures, re-edit the description of the Bayesian framework, some of the content moved to Appendix.
Krzysztof M. Graczyk, Kornel Witkowski
openaire   +2 more sources

Evaluation of Digital Technologies for Home‐Based Assessment in People With Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Digital technologies hold promise for transforming healthcare by enhancing personalized treatments and offer valuable opportunities to improve patient care. Here, we evaluated several novel, self‐administered, home‐based, digital endpoints for their association with corresponding conventional standard clinical measures (primary) in ...
Arne Mueller, Vanessa Vallejo, Mónica Povedano Panadés, Orla Hardiman, Véronique Danel‐Brunaud, Senda Ajroud‐Driss, Philippe Couratier, Jeremy Shefner, Anna Gokey, Mike DiCesare, Erin Lennox, Jens Praestgaard, Lucie Brujin, Peggy Allred, Ram Miller   +14 more
wiley   +1 more source

Sex‐Stratified Association of Regional Dopamine Transporter Binding With Disease Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To clarify the clinical relevance of dopamine transporter single‐photon emission computed tomography (DAT‐SPECT) abnormalities in amyotrophic lateral sclerosis (ALS), with a prespecified focus on sex‐stratified associations with disease progression and short‐term prognosis.
Tomoya Kawazoe, Keizo Sugaya, Kentaro Hayashi, Keiko Hino, Yasuhiro Nakata, Kota Bokuda, Toshio Shimizu, Kazushi Takahashi   +7 more
wiley   +1 more source

Physics-Informed Neural Networks for Quantum Control

Physical Review Letters
Quantum control is a ubiquitous research field that has enabled physicists to delve into the dynamics and features of quantum systems, delivering powerful applications for various atomic, optical, mechanical, and solid-state systems. In recent years, traditional control techniques based on optimization processes have been translated into efficient ...
Ariel Norambuena, Marios Mattheakis, Francisco J. González, Raúl Coto   +3 more
openaire   +3 more sources

White Matter Microstructural Abnormalities in Neonatal Onset Genetic Epilepsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Recent evidence indicates that epilepsy is associated with abnormal white matter. If seizures alter white matter, then the impact upon network function, epileptogenesis, and cognition could be pronounced in neonates undergoing rapid developmental myelination. Neonates with epilepsy due to nonstructural genetic causes provide a unique
Amanda G. Sandoval Karamian, Tianjia Zhu, Hao Huang, Shavonne L. Massey, Mark P. Fitzgerald, Darshana Parikh, Arastoo Vossough, Ingo Helbig, Nicholas S. Abend   +8 more
wiley   +1 more source

A 57‐Year‐Old Male With Behavioral Variant Frontotemporal Dementia and MATR3 and NOS3 Mutations

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT This report presents a case of behavioral variant frontotemporal dementia caused by mutations in the MATR3 and NOS3 genes, aiming to analyze its clinical manifestations and genetic characteristics. For a case presenting with personality changes and gait abnormalities as the initial symptoms, this study conducted a comprehensive analysis of its
Feifei Lin, Saie Huang
wiley   +1 more source

Towards Stable Training of Complex-Valued Physics-Informed Neural Networks: A Holomorphic Initialization Approach

Mathematics
This work introduces a new initialization scheme for complex-valued layers in physics-informed neural networks that use holomorphic activation functions.
Andrei-Ionuț Mohuț, Călin-Adrian Popa
doaj   +1 more source

Robust Variational Physics-Informed Neural Networks

Computer Methods in Applied Mechanics and Engineering
We introduce a Robust version of the Variational Physics-Informed Neural Networks method (RVPINNs). As in VPINNs, we define the quadratic loss functional in terms of a Petrov-Galerkin-type variational formulation of the PDE problem: the trial space is a (Deep) Neural Network (DNN) manifold, while the test space is a finite-dimensional vector space ...
Rojas, Sergio, Maczuga, Paweł, Muñoz-Matute, Judit, Pardo, David, Paszyński, Maciej   +4 more
openaire   +3 more sources

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

MODELING OF KOVAZHNY FLOW AND TAYLOR – GREEN VORTEX ON PHYSICS-INFORMED RADIAL BASIS FUNCTION NETWORKS

Модели, системы, сети в экономике, технике, природе и обществе
Background. An analysis of physics-informed neural networks for solving partial differential equations has been conducted, and the advantages of physics-informed radial basis function networks have been demonstrated.
Dmitry A. Stenkin
doaj   +1 more source