Results 101 to 110 of about 2,848,958 (338)
Advanced Functional Materials, EarlyView.We present a fully automated Bayesian optimization (BO) protocol for the parameterization of nonbonded interactions in coarse‐grain CG force fields (BACH). Using experimental thermophysical data, we apply the protocol to a broad range of liquids, spanning linear, branched, and unsaturated hydrocarbons, esters, triglycerides, and water.
Janak Prabhu +3 more
wiley +1 more source
On almost sure convergence rates for the kernel estimator of a covariance operator under negative association [PDF]
Journal of Mahani Mathematical ResearchIt is suppose that $\{X_n,~n\geq 1\}$ is a strictly stationary sequence of negatively associated random variables with continuous distribution function F.
Hadi Jabbari
doaj +1 more source
Fourier–Bessel heat kernel estimates
Journal of Mathematical Analysis and Applications, 2016 11 ...
Małecki, Jacek +2 more
openaire +2 more sources
Bioprinting Organs—Science or Fiction?—A Review From Students to Students
Advanced Healthcare Materials, EarlyView.Bioprinting artificial organs has the potential to revolutionize the medical field. This is a comprehensive review of the bioprinting workflow delving into the latest advancements in bioinks, materials and bioprinting techniques, exploring the critical stages of tissue maturation and functionality.
Nicoletta Murenu +18 more
wiley +1 more source
AxiomsThis paper investigates the asymptotic behavior of kernel-based estimators for the error distribution in a first-order autoregressive model with dependent errors. The model assumes that the error terms form an α-mixing sequence with an unknown cumulative
Bing Wang +4 more
doaj +1 more source
Nonparametric Estimation of Scalar Diffusion Processes of Interest Rates Using Asymmetric Kernels [PDF]
This paper proposes a nonparametric regression using asymmetric kernel functions for nonnegative, absolutely regular processes, and specializes this technique to estimating scalar diffusion models of spot interest rate.
Masayuki Hirukawa, Nikolay Gospodinov
core
Kernel methods in machine learning
, 2008 We review machine learning methods employing positive definite kernels. These methods formulate learning and estimation problems in a reproducing kernel Hilbert space (RKHS) of functions defined on the data domain, expanded in terms of a kernel.
Hofmann, Thomas +2 more
core +2 more sources
Unveiling the Role of Curvature in Carbon for Improved Energy Release of Ammonium Perchlorate
Advanced Materials, EarlyView.High‐curvature carbon materials identified via machine learning and simulation can enhance the heat release and combustion performance of ammonium perchlorate. ABSTRACT The catalytic role of carbon curvature in the thermal decomposition of ammonium perchlorate (AP) remains largely unexplored. To address this gap, this study employs machine learning and
Dan Liu +8 more
wiley +1 more source
Advanced Materials, EarlyView.AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source
Estimation of Weighted Extropy Under the α-Mixing Dependence Condition
StatsIntroduced as a complementary concept to Shannon entropy, extropy provides an alternative perspective for measuring uncertainty. While useful in areas such as reliability theory and scoring rules, extropy in its original form treats all outcomes equally,
Radhakumari Maya +3 more
doaj +1 more source