Results 91 to 100 of about 36,851 (159)

Free Choice in Quantum Theory: A p-adic View. [PDF]

Entropy (Basel), 2023
Anashin V.
europepmc   +1 more source

Lipschitz‐free spaces over strongly countable‐dimensional spaces and approximation properties

Bulletin of the London Mathematical Society
Abstract Let be a compact, metrisable and strongly countable‐dimensional topological space. Let be the set of all metrics on compatible with its topology, and equip with the topology of uniform convergence, where the metrics are regarded as functions on .
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A Choquet theory of Lipschitz-free spaces

Let $(M,d)$ be a complete metric space and let $\mathcal{F}(M)$ denote the Lipschitz-free space over $M$. We develop a ``Choquet theory of Lipschitz-free spaces'' that draws from the classical Choquet theory and the De Leeuw representation of elements of $\mathcal{F}(M)$ (and its bidual) by positive Radon measures on $β\widetilde{M}$, where $\widetilde{
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Lipschitz-free spaces and Bossard's reduction argument

Motivated by recent work of E. Basset, G. Lancien and A. Procházka, we use the reduction argument of Bossard to prove two results: if a separable Banach space is isomorphically universal for the class of Lipschitz-free spaces over the countable complete discrete metric spaces then it is isomorphically universal for the class of separable Banach spaces,
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Varifold solutions to volume-preserving mean curvature flow: existence and weak-strong uniqueness. [PDF]

Math Ann
Poiatti A.
europepmc   +1 more source

No-rank tensor decomposition via metric learning. [PDF]

Sci Rep
Bagherian M.
europepmc   +1 more source

Continuous Operators from Spaces of Lipschitz Functions. [PDF]

Results Math
Bargetz C, Kąkol J, Sobota D.
europepmc   +1 more source

Nonlinear SPDEs and Maximal Regularity: An Extended Survey. [PDF]

Nonlinear Differ Equ Appl
Agresti A, Veraar M.
europepmc   +1 more source

Continuity up to the boundary for minimizers of the one-phase Bernoulli problem. [PDF]

Calc Var Partial Differ Equ
Fernández-Real X, Gruen F.
europepmc   +1 more source

Leveraging network motifs to improve artificial neural networks. [PDF]

Nat Commun
Zhang H, Yang CH, Zenil H, Chen PY, Shen Y, Kiani NA, Tegnér JN.   +6 more
europepmc   +1 more source