Results 231 to 240 of about 63,696 (324)
Reproducing kernels, de Branges-Rovnyak spaces, and norms of weighted composition operators
Michael T. Jury
openalex +2 more sources
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir +4 more
wiley +1 more source
New Properties of Holomorphic Sobolev-Hardy Spaces. [PDF]
Gryc W, Lanzani L, Xiong J, Zhang Y.
europepmc +1 more source
Nonlinear functional models for functional responses in reproducing kernel Hilbert spaces
Heng Lian
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Deep Learning‐Assisted Coherent Raman Scattering Microscopy
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
Kernel-FastICA-Based Nonlinear Blind Source Separation for Anti-Jamming Satellite Communications. [PDF]
Sun X, Li C, Li J, Su Q.
europepmc +1 more source
Reproducing kernel particle method with complex variables for elasticity
C. C. Li, Yumin Cheng
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Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz +4 more
wiley +1 more source
A class of tridiagonal reproducing kernels
Gregory T. Adams, Paul McGuire
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Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley +1 more source

