Results 71 to 80 of about 1,059,681 (321)
The Dunkl kernel and intertwining operator for dihedral groups
, 2020 Dunkl operators associated with finite reflection groups generate a commutative algebra of differential-difference operators. There exists a unique linear operator called intertwining operator which intertwines between this algebra and the algebra of ...
De Bie, Hendrik, Lian, Pan
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Simplified, automated methods for assessing pixel intensities of fluorescently-tagged drugs in cells. [PDF]
PLoS ONE, 2018 Assessing the cytoplasmic uptake of fluorescently-tagged drugs in heterogeneous cell types currently involves time-consuming manual segmentation of confocal microscopy images.
Allan Kachelmeier +5 more
doaj +1 more source
kProbLog: An Algebraic Prolog for Kernel Programming [PDF]
, 2016 kProbLog is a simple algebraic extension of Prolog with facts and rules annotated with semiring labels. We propose kProbLog as a language for learning with kernels. kProbLog allows to elegantly specify systems of algebraic expressions on databases. We propose some code examples of gradually increasing complexity, we give a declarative specification of ...
Luc De Raedt +3 more
openaire +3 more sources
International Journal of Adaptive Control and Signal Processing, EarlyView.Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez +2 more
wiley +1 more source
Group Classification of the Unsteady Axisymmetric Boundary Layer Equation
MathematicsUnsteady equations of flat and axisymmetric boundary layers are considered. For the unsteady axisymmetric boundary layer equation, the problem of group classification is solved. It is shown that the kernel of symmetry operators can be extended by no more
Alexander V. Aksenov, Anatoly A. Kozyrev
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Improvement of variables interpretability in kernel PCA
BMC Bioinformatics, 2023 Background Kernel methods have been proven to be a powerful tool for the integration and analysis of high-throughput technologies generated data. Kernels offer a nonlinear version of any linear algorithm solely based on dot products.
Mitja Briscik +2 more
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Bulletin of the Section of Logic, 2021 Hilbert algebras are important tools for certain investigations in intuitionistic logic and other non-classical logic and as a generalization of Hilbert algebra a new algebraic structure, called a GE-algebra (generalized exchange algebra), is introduced ...
Ravikumar Bandaru +2 more
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Elliptic Ding-Iohara Algebra and the Free Field Realization of the Elliptic Macdonald Operator [PDF]
, 2013 The Ding-Iohara algebra is a quantum algebra arising from the free field realization of the Macdonald operator. Starting from the elliptic kernel function introduced by Komori, Noumi and Shiraishi, we can define an elliptic analog of the Ding-Iohara ...
Saito, Yosuke
core
Algebraic monoids with group kernels
Semigroup Forum, 1996 Let \(M\) be an algebraic monoid, that is \(M\) be both an affine variety over an algebraically closed field \(K\) and a monoid for which the operation of multiplication \(M\times M\to M\) is an affine variety morphism. An algebraic monoid \(M\) is irreducible if it is so as an affine variety. \(M\) is regular if \(a\in aMa\) for all \(a\in M\).
openaire +2 more sources
AI‐Driven Defect Engineering for Advanced Thermoelectric Materials
Advanced Materials, EarlyView.This review presents how AI accelerates the design of defect‐tuned thermoelectric materials. By integrating machine learning with high‐throughput data and physics‐informed representations, it enables efficient prediction of thermoelectric performance from complex defect landscapes.
Chu‐Liang Fu +9 more
wiley +1 more source