Results 141 to 150 of about 554,174 (252)
Nonparametric Beta kernel estimator for long memory time series [PDF]
The paper introduces a new nonparametric estimator of the spectral density that is given in smoothing the periodogram by the probability density of Beta random variable (Beta kernel).
VAN BELLEGEM, Sébastien +1 more
core
Chunking-Synthetic Approaches to Large-Scale Kernel Machines [PDF]
, 2000 We consider a kernel-based approach to nonlinear classification that combines the generation of ?synthetic? points (to be used in the kernel) with ?chunking?
Gonzalez-Castano, Francisco +1 more
core
Advanced Materials Technologies, EarlyView.A physics‐informed generative framework introduces Directional Latent Hybridization (DLH) for the deterministic inverse design of nonlinear metamaterials. By hybridizing dominant traits from parent geometries in the latent space, DLH overcomes the instabilities of stochastic models to ensure high structural precision at high densities.
Semin Ahn +2 more
wiley +1 more source
Advanced Materials Technologies, EarlyView.Dense tactile streams from across the humanoid body converge on collide in a central wiring and data bottleneck. By relocating computation closer to and then into the skin itself, near‐ and in‐sensor architectures, together with neuromorphic computing, chart a path toward perception‐native electronic skin, in which the conversion of stimulus into ...
Mijin Kim +6 more
wiley +1 more source
Abstract The signature kernel is a positive definite kernel for sequential data. It inherits theoretical guarantees from stochastic analysis, has efficient algorithms for computation, and shows strong empirical performance. In this chapter, we provide an introduction to the signature kernel by highlighting the analytic connection ...
Darrick Lee, Harald Oberhauser
openaire +3 more sources
Application of kernel-based Bayesian optimization in 3D CZT SPECT reconstructions [PDF]
openApplication of kernel-based Bayesian optimization in 3D CZT SPECT reconstructionsApplication of kernel-based Bayesian optimization in 3D CZT SPECT ...
PASTRELLO, LUCA
core
On‐Chip Photonic Neural Network Architectures
Advanced Optical Materials, EarlyView.This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong +7 more
wiley +1 more source
A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation. [PDF]
Multivariate kernel regression is an important tool for investigating the relationship between a response and a set of explanatory variables. It is generally accepted that the performance of a kernel regression estimator largely depends on the choice of ...
Robert D. Brooks +2 more
core
Advanced Optical Materials, EarlyView.A dioxolane‐mediated reaction synthesis provides a simple and scalable route to phase‐pure Cs3Cu2Cl5 scintillator powders with near‐complete conversion, near‐unity photoluminescence quantum yield, and long‐term stability. The resulting green‐emitting composite films exhibit strong radioluminescence, high light yield, and practical compatibility with ...
Young Seung Choi +12 more
wiley +1 more source