Regularity in metric spaces

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We prove a sharp quantitative version of the Faber–Krahn inequality for the short-time Fourier transform (STFT). To do so, we consider a deficit which measures by how much the STFT of a function fails to be optimally concentrated on an arbitrary set of pos ...

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We construct a measure on the thick points of a Brownian loop soup in a bounded domain D

D

of the plane with given intensity theta>0

\theta >0

, which is formally obtained by exponentiating the square root of its occupation field. The measure is construct ...

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The beta spectrum of the main transition of the 171Tm was measured using a double focalizing spectrometer. The instrument was lately improved in order to reduce its low energy threshold to 34 keV. We used the spectrometer to measure the energy end-point of ...

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We consider nonlinear parabolic stochastic PDEs on a bounded Lipschitz domain driven by a Gaussian noise that is white in time and colored in space, with Dirichlet or Neumann boundary condition. We establish existence, uniqueness and moment bounds of the r ...

Regularity in metric spaces

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Geometric Learning: Leveraging differential geometry for learning and control

Efficient and insightful descriptors for representing molecular and material space

Anomalous and Chern topological waves in hyperbolic networks

Stability of the Faber-Krahn inequality for the short-time Fourier transform

Resolving the vicinity of supermassive black holes with gravitational microlensing

Small-amplitude Red Giants Elucidate the Nature of the Tip of the Red Giant Branch as a Standard Candle

WILD SOLUTIONS TO SCALAR EULER-LAGRANGE EQUATIONS

Extensions of Peer Prediction Incentive Mechanisms

Cochains are all you need

Debates on the dorsomedial prefrontal/dorsal anterior cingulate cortex: insights for future research

Multiplicative chaos of the Brownian loop soup

Appropriations and Uses of Travel Time

Measurement of the 171Tm beta spectrum

THE PHASE TRANSITION FOR PLANAR GAUSSIAN PERCOLATION MODELS WITHOUT FKG

Stability of Image-Reconstruction Algorithms

Stable parameterization of continuous and piecewise-linear functions

Fairness and Explainability in Clustering Problems

Complex Representation Learning with Graph Convolutional Networks for Knowledge Graph Alignment

Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks

Parabolic stochastic PDEs on bounded domains with rough initial conditions: moment and correlation bounds