Results 111 to 120 of about 43,843 (275)
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
Advanced Intelligent Discovery, EarlyView.This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Comparing Penalized Splines and Fractional Polynomials for Flexible Modelling of the Effects of Continuous Predictor Variables [PDF]
, 2010 P(enalized)-splines and fractional polynomials (FPs) have emerged as powerful smoothing techniques with increasing popularity in several fields of applied research.
Lang, Stefan +3 more
core
An algorithm for a constrained P-spline
BIT Numerical MathematicsAbstract Regression splines are largely used to investigate and predict data behavior, attracting the interest of mathematicians for their beautiful numerical properties, and of statisticians for their versatility with respect to the applications.
Campagna, Rosanna +4 more
openaire +2 more sources
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.It is a fact that slippage causes tracking errors in both longitudinal and lateral directions which results to have less travel distance in tracking a reference trajectory. Less travel distance means having energy loss of the battery and carrying loads less than planned.
Gokhan Bayar +2 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.This work presents a robot‐assisted Doppler optical coherence tomography system for autonomous, wide‐field intraoperative assessment of microvascular anastomoses. Machine‐vision–guided probe positioning and adaptive scan planning enable three‐dimensional structural and hemodynamic imaging over extended vessel segments.
Xiaochen Li +10 more
wiley +1 more source
Spatially Adaptive Bayesian P-Splines with Heteroscedastic Errors [PDF]
, 2004 An increasingly popular tool for nonparametric smoothing are penalized splines (P-splines) which use low-rank spline bases to make computations tractable while maintaining accuracy as good as smoothing splines.
Carroll, Raymond J. +2 more
core +1 more source
Sketching for Kronecker Product Regression and P-splines
, 2017 TensorSketch is an oblivious linear sketch introduced in Pagh'13 and later used in Pham, Pagh'13 in the context of SVMs for polynomial kernels. It was shown in Avron, Nguyen, Woodruff'14 that TensorSketch provides a subspace embedding, and therefore can be used for canonical correlation analysis, low rank approximation, and principal component ...
Diao, Huaian +3 more
openaire +2 more sources
A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks
Advanced Intelligent Systems, EarlyView.This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan +6 more
wiley +1 more source
Frontiers in Public HealthIntroductionThere is evidence suggesting that Bisphenol A (BPA) is associated with increased all-cause mortality in adults. However, the specific nature of the relationship between BPA exposure and cancer mortality remains relatively unexplored ...
Ying Yuan +4 more
doaj +1 more source
Nonparametric estimation of mean and dispersion functions in extended generalized linear models. [PDF]
In this paper the interest is in regression analysis for data that show possibly overdispersion or underdispersion. The starting point for modeling are generalized linear models in which we no longer admit a linear form for the mean regression function ...
Claeskens, Gerda +2 more
core