Results 141 to 150 of about 124,089 (295)
Advanced Intelligent Discovery, EarlyView.A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri +6 more
wiley +1 more source
A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
Advanced Intelligent Discovery, EarlyView.The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
wiley +1 more source
Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology
Advanced Intelligent Discovery, EarlyView.Energy efficient computing has driven a shift toward brain‐inspired neuromorphic hardware. This study explores the design of three distinct silicon neuron topologies implemented in 16 nm fin field‐Effect transistor technology. While the Axon‐Hillock design achieves gigahertz throughput, its functional fragility persists. The Morris–Lecar model captures
Logan Larsh +3 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.To enable versatile unconventional computing, a single SiOx threshold switching device is engineered to exhibit controllable dual‐mode oscillation. By modulating the input voltage, the device selectively provides stable full oscillation for oscillatory neural networks and stochastic probabilistic oscillation for probabilistic bits and true random ...
Hyeonsik Choi +3 more
wiley +1 more source
Skew selection for factor stochastic volatility models. [PDF]
J Appl Stat, 2020 Nakajima J.
europepmc +1 more source
A note on the Malliavin differentiability of the Heston volatility [PDF]
We show that the Heston volatility or equivalently the Cox-Ingersoll-Ross process is Malliavin differentiable and give an explicit expression for the derivative.
Christian-Olivier Ewald, Elisa Alòs
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A multi-country dynamic factor model with stochastic volatility for euro area business cycle analysis. [PDF]
J Forecast, 2020 Huber F, Pfarrhofer M, Piribauer P.
europepmc +1 more source
Advanced Intelligent Systems, EarlyView.The approach of physical in materia computing incorporates parallel computing within the medium itself. A scalable and energy‐efficient, oxide‐based computational platform is realized in form of a nanoporous network of volatile niobium oxide memristors sandwiched between top and bottom metallic electrodes, and then tested for prediction and ...
Joshua Donald +7 more
wiley +1 more source
Nonparametric methods for volatility density estimation
, 2009 Stochastic volatility modelling of financial processes has become increasingly popular. The proposed models usually contain a stationary volatility process.
Spreij, Peter +2 more
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