Results 51 to 60 of about 13,144,199 (261)
Advanced Intelligent Discovery, EarlyView.A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley +1 more source
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
A Liouville-Gelfand Equation for $k$-Hessian Operators
Rocky Mountain Journal of Mathematics, 2004 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +3 more sources
Advanced Intelligent Systems, EarlyView.This study presents an integrated proof‐of‐concept robotic platform for targeted delivery applications. A hybrid magnetic actuation system achieves single‐input (z) multistate stabilization (x, y, ϕ, and θ) for precise capsule transport with submillimeter positioning accuracy.
Sejun Park +6 more
wiley +1 more source
Vector‐Based SparseGPT: A Vector‐Based Sparsity Method for Large Language Model
Advanced Intelligent Systems, EarlyView.Conventional pruning such as SparseGPT produces harmful accumulated errors through step‐by‐step weight editing. V‐SparseGPT prunes and updates target weights simultaneously to curb these errors for N:M structured sparsity. Block‐sparsity and layer‐parallel sparsity greatly boost pruning efficiency.
Junfei He +3 more
wiley +1 more source
Generalized Minkowski inequality via degenerate Hessian equations on exterior domains [PDF]
, 2022 In this paper, we prove a generalized Minkowski inequality holds for any smooth, $(k-1)$-convex, starshaped domain $\Omega.$ Our proof relies on the solvability of the degenerate $k$-Hessian equation on the exterior domain $\mathbb R^n\setminus\Omega.
Xiao, Ling
core +1 more source
Polyharmonic $k-$Hessian equations in $\mathbb{R}^N$
, 2016 This work is focused on the study of the nonlinear elliptic higher order equation \begin{equation}\nonumber \left( -Δ\right)^m u = S_k[-u] + λf, \qquad x \in \mathbb{R}^N, \end{equation} where the $k-$Hessian $S_k[u]$ is the $k^{\mathrm{th}}$ elementary symmetric polynomial of eigenvalues of the Hessian matrix of the solution and the datum $f$ belongs ...
Balodis, Pedro, Escudero, Carlos
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The exterior Dirichlet problem for the homogeneous $k$-Hessian equation [PDF]
We study the exterior Dirichlet problem for the homogeneous $k$-Hessian equation. The prescribed asymptotic behavior at infinity of the solution is zero if $k\frac{n}{2}$.
Ma, Xi-Nan, Zhang, Dekai
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Multiplicity of bounded solutions to the $k$-Hessian equation with a Matukuma-type source [PDF]
Revista Matemática Iberoamericana, 2019 The aim of this paper is to deal with the k -Hessian counterpart of the Laplace equation involving a nonlinearity studied by Matukuma. Namely, our model is the problem (
Miyamoto, Yasuhito +2 more
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Biotechnology and Bioengineering, EarlyView.ABSTRACT Accurate prediction of bioprocess scale‐up is critical for accelerating the deployment of novel and sustainable biomanufacturing systems. However, this remains challenging as multi‐scale data is expensive to generate and mechanistic understanding is often incomplete, leading upscaling decisions to rely heavily on empirical expertise. This work
Harvey Al‐Ramadhan +3 more
wiley +1 more source