Results 161 to 170 of about 107,251 (304)

Global Universality of the Two-Layer Neural Network with the k-Rectified Linear Unit

open access: yesJournal of Function Spaces
This paper concerns the universality of the two-layer neural network with the k-rectified linear unit activation function with k=1,2,… with a suitable norm without any restriction on the shape of the domain in the real line. This type of result is called
Naoya Hatano   +3 more
doaj   +1 more source

Volume Dimension of Mass Functions in Complex Networks

open access: yesMathematics
A novel definition of volume dimension for a mass function based on a sigmoid asymptote is proposed; in particular, we extend the volume dimension of a mass function to define the volume dimensions for nodes and edges in complex networks.
Maria del Carmen Soto-Camacho   +3 more
doaj   +1 more source

Evaluation of product of two sigmoidal membership functions (psigmf) as an ANFIS membership function for prediction of nanofluid temperature [PDF]

open access: gold, 2020
Meisam Babanezhad   +4 more
openalex   +1 more source

Data‐Driven Feedback Identifies Focused Ultrasound Exposure Regimens for Improved Nanotheranostic Targeting of the Brain

open access: yesAdvanced Science, EarlyView.
Machine learning models predict in real time the onset of harmful microbubble collapse during microbubble‐enhanced focused ultrasound (MB‐FUS) and enable dynamic adjustment of sonication to prevent cavitation‐induced damage. This predictive control expands the safe operating window for bloodbrain barrier opening, enhancing nanoparticle delivery and ...
Hohyun Lee   +17 more
wiley   +1 more source

Multi‐View Biomedical Foundation Models for Molecule‐Target and Property Prediction

open access: yesAdvanced Science, EarlyView.
Molecular foundation models can provide accurate predictions for a large set of downstream tasks. We develop MMELON, an approach that integrates pre‐trained graph, image, and text foundation models and validate our multi‐view model on over 120 tasks, including GPCR binding.
Parthasarathy Suryanarayanan   +17 more
wiley   +1 more source

Machine Learning‐Enhanced Analysis of Exosomal Surface Sialic Acid Using Surface‐Enhanced Raman Spectroscopy for Ovarian Cancer Diagnosis and Therapeutic Monitoring

open access: yesAdvanced Science, EarlyView.
Machine learning‐assisted surface‐enhanced Raman spectroscopy analysis of exosomal sialic acid for ovarian cancer diagnosis, as well as independent monitoring of exosomal sialic acid expression levels across different treatment periods, reveals a potential correlation with treatment response.
Lili Cong   +6 more
wiley   +1 more source

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