Results 171 to 180 of about 851,945 (325)
Kolmogorov–Arnold Network for Transistor Compact Modeling
This work introduces Kolmogorov–Arnold network (KAN) for the transistor—an architecture that integrates interpretability with high precision in physics‐based function modeling. The results reveal that despite achieving superior prediction accuracy for critical figures of merit, KAN demonstrates unique inherent challenges for transistor modeling ...
Rodion Novkin, Hussam Amrouch
wiley +1 more source
Quasisymmetries of finitely ramified Julia sets. [PDF]
Belk J, Forrest B.
europepmc +1 more source
This work harnesses nonidealities in analog in‐memory computing (IMC) by training physical neural networks modeled with ordinary differential equations. A differentiable spike‐time discretization accelerates training by 20× and reduces memory usage by 100×, enabling large IMC‐equivalent models to learn the CIFAR‐10 dataset.
Yusuke Sakemi +5 more
wiley +1 more source
Delaunay-Like Compact Equilibria in the Liquid Drop Model. [PDF]
Del Pino M, Musso M, Zuniga A.
europepmc +1 more source
This study presents BiT‐HyMLPKANClassifier, a novel hybrid deep learning framework for automated human peripheral blood cell classification. Model combines Big Transfer models with multilayer perceptron and efficient Kolmogorov–Arnold Network architectures, achieving over 97% accuracy.
Ömer Miraç KÖKÇAM, Ferhat UÇAR
wiley +1 more source
Fixed point theorems for nonself G-almost contractive mappings in Banach spaces endowed with graphs
JUKRAPONG TIAMMEE +2 more
openalex +1 more source
On a Countable Sequence of Homoclinic Orbits Arising Near a Saddle-Center Point. [PDF]
Baldomá I, Guardia M, Pelinovsky DE.
europepmc +1 more source
A Robotic Urinary Bladder Enabling Volume Monitoring and Assisted Micturition
An implantable robotic bladder is presented that can store urine in an origami‐designed enclosure. An inductance sensing principle can monitor and transfer the urine volume in real‐time. It can actively expand based on the amount of urine collected from kidneys and apply on‐demand mechanical compression to assist urination.
Izadyar Tamadon +4 more
wiley +1 more source
From Droplet to Diagnosis: Spatio‐Temporal Pattern Recognition in Drying Biofluids
This article integrates machine learning (ML) with the spatio‐temporal evolution of biofluid droplets to reveal how drying and self‐assembly encode distinctive compositional fingerprints. By leveraging textural features and interpretable ML, it achieves robust classification of blood abnormalities with over 95% accuracy.
Anusuya Pal +2 more
wiley +1 more source

