Results 221 to 230 of about 315,258 (298)
Convergence properties of dynamic mode decomposition for analytic interval maps
Abstract Extended dynamic mode decomposition (EDMD) is a data‐driven algorithm for approximating spectral data of the Koopman operator associated to a dynamical system, combining a Galerkin method with N$N$ functions and a quadrature method with M$M$ quadrature nodes.
Elliz Akindji +3 more
wiley +1 more source
Some Properties of the Plaquette Random-Cluster Model. [PDF]
Duncan P, Schweinhart B.
europepmc +1 more source
Dimer models and conformal structures
Abstract Dimer models have been the focus of intense research efforts over the last years. Our paper grew out of an effort to develop new methods to study minimizers or the asymptotic height functions of general dimer models and the geometry of their frozen boundaries.
Kari Astala +3 more
wiley +1 more source
Integral Betti signatures of brain, climate and financial networks compared to hyperbolic, Euclidean and spherical models. [PDF]
Caputi L, Pidnebesna A, Hlinka J.
europepmc +1 more source
Incorporating Scale Uncertainty into Differential Expression Analyses Using ALDEx2
Abstract Differential abundance or expression analyses are routinely performed on metagenomic, metatranscriptomic, and amplicon sequencing data. In such datasets, analysts usually have no information regarding the true scale (i.e., size) of the microbial community or sample under study, with inter‐sample differences in sequencing depth instead being ...
Scott J. Dos Santos, Gregory B. Gloor
wiley +1 more source
Scalar wave diffraction by an open-ended sphere-conical cavity: the Abel integral transform in the Dirichlet and Neumann problems. [PDF]
Kuryliak D, Lysechko V.
europepmc +1 more source
On the Q‐Polynomial Property of Bipartite Graphs Admitting a Uniform Structure
ABSTRACT Let Γ denote a finite, connected graph with vertex set X. Fix x ∈ X and let ε ≥ 3 denote the eccentricity of x. For mutually distinct scalars { θ i * } i = 0 ε define a diagonal matrix A * = A * ( θ 0 * , θ 1 * , … , θ ε * ) ∈ Mat X ( R ) as follows: for y ∈ X we let ( A * ) y y = θ ∂ ( x , y ) *, where ∂ denotes the shortest path length ...
Blas Fernández +3 more
wiley +1 more source
Maximum likelihood estimation of log-affine models using detailed-balanced reaction networks. [PDF]
Henriksson O +3 more
europepmc +1 more source

