Publications associées à Espace localement compact

On distributional autoregression and iterated transportation

We consider the problem of defining and fitting models of autoregressive time series of probability distributions on a compact interval of Double-struck capital R. An order-1 autoregressive model in this context is to be understood as a Markov chain, where ...

Hoboken2024

NbN films with high kinetic inductance for high-quality compact superconducting resonators

Edoardo Charbon, Pasquale Scarlino, Fabrizio Minganti, Simone Frasca, Marco Scigliuzzo, Vincent Jean Yves Jouanny, Fabian Oppliger, Roberto Musio

Niobium nitride (NbN) is a particularly promising material for quantum technology applications, as it shows the degree of reproducibility necessary for large-scale superconducting circuits. We demonstrate that resonators based on NbN thin films present a o ...

2023

Distributional Regression and Autoregression via Optimal Transport

Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

EPFL2023

A type I conjecture and boundary representations of hyperbolic groups

Nicolas Monod

We establish new results on the weak containment of quasi-regular and Koopman representations of a second countable locally compact group G

G

associated with nonsingular G

G

-spaces. We deduce that any two boundary representations of a hyperbolic locally ...

WILEY2023

Universal Approximation Property of Hamiltonian Deep Neural Networks

Giancarlo Ferrari Trecate, Muhammad Zakwan

This letter investigates the universal approximation capabilities of Hamiltonian Deep Neural Networks (HDNNs) that arise from the discretization of Hamiltonian Neural Ordinary Differential Equations. Recently, it has been shown that HDNNs enjoy, by design, ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Compact, Spatial-mode-interaction-free, Ultralow-loss, Nonlinear photonic integrated circuits

Tobias Kippenberg, Rui Ning Wang, Xinru Ji, Zheru Qiu, Junqiu Liu, Jijun He

We implement Euler bends to build compact high-Q Si3N4 racetrack microresonators, featuring a small footprint of only 0.21 mm(2) for 19.8 GHz FSR. We demonstrate that these multi-mode microresonators can be operated in the single-mode regime and generate a ...

IEEE2022

Localization errors of the stochastic heat equation

David Jean-Michel Candil

In this thesis, we study the stochastic heat equation (SHE) on bounded domains and on the whole Euclidean space

\R^d.

We confirm the intuition that as the bounded domain increases to the whole space, both solutions become arbitrarily close to one another ...

EPFL2022

Maximizing friction by liquid flow clogging in confinement

Ignacio Pagonabarraga Mora, Xiaoqi Zhang, Shan Chen

In the nanoscale regime, flow behaviors for liquids show qualitative deviations from bulk expectations. In this work, we reveal by molecular dynamics simulations that plug flow down to nanoscale induces molecular friction that leads to a new flow structure ...

SPRINGER2022

Compact, spatial-mode-interaction-free, ultralow-loss, nonlinear photonic integrated circuits

Tobias Kippenberg, Rui Ning Wang, Xinru Ji, Zheru Qiu, Junqiu Liu, Jijun He

Multi-mode waveguides are ubiquitously used in integrated photonics. Although interaction among different spatial waveguide eigenmodes can induce novel nonlinear phenomena, spatial mode interaction is typically undesired. Adiabatic bends, such as Euler ben ...

NATURE PORTFOLIO2022

A Topological characterisation of Weisfeiler-Leman equivalence classes

Graph Neural Networks (GNNs) are learning models aimed at processing graphs and signals on graphs. The most popular and successful GNNs are based on message passing schemes. Such schemes inherently have limited expressive power when it comes to distinguish ...

2022

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On distributional autoregression and iterated transportation

NbN films with high kinetic inductance for high-quality compact superconducting resonators

Distributional Regression and Autoregression via Optimal Transport

A type I conjecture and boundary representations of hyperbolic groups

Universal Approximation Property of Hamiltonian Deep Neural Networks

Compact, Spatial-mode-interaction-free, Ultralow-loss, Nonlinear photonic integrated circuits

Localization errors of the stochastic heat equation

Maximizing friction by liquid flow clogging in confinement

Compact, spatial-mode-interaction-free, ultralow-loss, nonlinear photonic integrated circuits

A Topological characterisation of Weisfeiler-Leman equivalence classes

Maximizing friction by liquid flow clogging in confinement

On distributional autoregression and iterated transportation

Localization errors of the stochastic heat equation

A Topological characterisation of Weisfeiler-Leman equivalence classes

Distributional Regression and Autoregression via Optimal Transport

Universal Approximation Property of Hamiltonian Deep Neural Networks

NbN films with high kinetic inductance for high-quality compact superconducting resonators

A type I conjecture and boundary representations of hyperbolic groups

Compact, Spatial-mode-interaction-free, Ultralow-loss, Nonlinear photonic integrated circuits

Compact, spatial-mode-interaction-free, ultralow-loss, nonlinear photonic integrated circuits