Results 121 to 130 of about 120,097 (295)
Improved HAC Covariance Matrix Estimation Based on Forecast Errors [PDF]
We propose computing HAC covariance matrix estimators based on one-stepahead forecasting errors. It is shown that this estimator is consistent and has smaller bias than other HAC estimators.
Chung-Ming Kuan, Yu-Wei Hsieh
core
Screen gate‐based transistors are presented, enabling tunable analog sigmoid and Gaussian activations. The SA‐transistor improves MRI classification accuracy, while the GA‐transistor supports precise Gaussian kernel tuning for forecasting. Both functions are implemented in a single device, offering compact, energy‐efficient analog AI processing ...
Junhyung Cho +9 more
wiley +1 more source
Bandwidth Selection Problem for Nonparametric Regression Model with Right-Censored Data [PDF]
In this paper, the proposed estimator for the unknown nonparametric regression function is a Nadarya-Watson (Nadarya, 1964; Watson, 1964) type kernel estimator. In this estimation procedure, the censored observations are replaced by synthetic data points
Dursun AYDIN, Ersin YILMAZ
doaj
Kernel Estimators for Cell Probabilities
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources
A neuromorphic computing system exploiting opto‐ionic modulation in lead halide perovskite microcrystals demonstrates high‐dimensional reservoir dynamics with diffraction‐limited node resolution. Leveraging ultrafast excited‐state interactions, it achieves efficient computation (800 pJ/node‐operation), robustly distinguishing 4‐bit pulse sequences ...
Philipp Kollenz +7 more
wiley +1 more source
Navigating Ternary Doping in Li‐ion Cathodes With Closed‐Loop Multi‐Objective Bayesian Optimization
The search for advanced battery materials is pushing us into highly complex composition spaces. Here, a space with about 14 million unique combinations is efficiently explored using high‐throughput experimentation guided by Bayesian optimization with a deep kernel trained on both the Materials Project database and our data.
Nooshin Zeinali Galabi +6 more
wiley +1 more source
Recent Progress on Flexible Multimodal Sensors: Decoupling Strategies, Fabrication and Applications
In this review, we establish a tripartite decoupling framework for flexible multimodal sensors, which elucidates the underlying principles of signal crosstalk and their solutions through material design, structural engineering, and AI algorithms. We also demonstrate its potential applications across environmental monitoring, health monitoring, human ...
Tao Wu +10 more
wiley +1 more source
Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data
Estimating spot covariance is an important issue to study, especially with the increasing availability of high-frequency financial data. We study the estimation of spot covariance using a kernel method for high-frequency data.
Mustafayeva, Konul, Wang, Weining
core
Superionic Amorphous Li2ZrCl6 and Li2HfCl6
Amorphous Li2HfCl6 and L2ZrCl6 are shown to be promising solid‐state electrolytes with predicted ionic conductivities >20 mS·cm−1. Molecular dynamics simulations with machine‐learning force fields reveal that anion vibrations and flexible MCl6 octahedra soften the Li coordination cage and enhance mobility. Correlation between Li‐ion diffusivity and the
Shukai Yao, De‐en Jiang
wiley +1 more source
Here, we present a nanotechnology approach to construct synthetic lipid rafts on the live T cell membrane, leveraging a versatile DNA origami‐enabled platform named as the “cholesterol nano‐patch” (CNP). Our investigation highlights the effectiveness of DNA nanotechnology in exploring the impact of nanoscale arrangement of cholesterols on the ...
Yunmin Jung +4 more
wiley +1 more source

