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Publications associées (83)

Bounded and unbounded cohomology of homeomorphism and diffeomorphism groups

We determine the bounded cohomology of the group of homeomorphisms of certain low-dimensional manifolds. In particular, for the group of orientation-preserving homeomorphisms of the circle and of the closed 2-disc, it is isomorphic to the polynomial ring g ...

SPRINGER HEIDELBERG2023

Generative power of a protein language model trained on multiple sequence alignments

Anne-Florence Raphaëlle Bitbol, Damiano Sgarbossa, Umberto Lupo

Computational models starting from large ensembles of evolutionarily related protein sequences capture a representation of protein families and learn constraints associated to protein structure and function. They thus open the possibility for generating no ...

eLIFE SCIENCES PUBL LTD2023

A Künneth theorem for configuration spaces

Kathryn Hess Bellwald

We construct a spectral sequence converging to the homology of the ordered configuration spaces of a product of parallelizable manifolds. To identify the second page of this spectral sequence, we introduce a version of the Boardman-Vogt tensor product for ...

2022

Computational tools for twisted topological Hochschild homology of equivariant spectra

Kathryn Hess Bellwald, Inbar Klang

Twisted topological Hochschild homology of Cn-equivariant spectra was introduced by Angeltveit, Blumberg, Gerhardt, Hill, Lawson, and Mandell, building on the work of Hill, Hopkins, and Ravenel on norms in equivariant homotopy theory. In this paper we intr ...

ELSEVIER2022

A Shadow Perspective on Equivariant Hochschild Homologies

Kathryn Hess Bellwald, Inbar Klang

Shadows for bicategories, defined by Ponto, provide a useful framework that generalizes classical and topological Hochschild homology. In this paper, we define Hochschild-type invariants for monoids in a symmetric monoidal, simplicial model category V, as ...

OXFORD UNIV PRESS2022

Generalised Implicit Neural Representations

Pierre Vandergheynst

We consider the problem of learning implicit neural representations (INRs) for signals on non-Euclidean domains. In the Euclidean case, INRs are trained on a discrete sampling of a signal over a regular lattice. Here, we assume that the continuous signal e ...

2022

Performance and reproducibility of C-13 and N-15 hyperpolarization using a cryogen-free DNP polarizer

Hikari Ananda Infinity Yoshihara, Arianna Ferrari

The setup, operational procedures and performance of a cryogen-free device for producing hyperpolarized contrast agents using dissolution dynamic nuclear polarization (dDNP) in a preclinical imaging center is described. The polarization was optimized using ...

NATURE PORTFOLIO2022

Dosimetry modeling and experimental validation for the PETALE program in the CROCUS reactor

Andreas Pautz, Vincent Pierre Lamirand, Pavel Frajtag, Axel Guy Marie Laureau

The PETALE experimental program in the CROCUS reactor intends to provide integral measurements on reactivity worth and dosimetry measurement to constrain nuclear data relative to stainless steel heavy reflectors. The experimental setup consists in eight su ...

2021

The completeness of the generalized eigenfunctions and an upper bound for the counting function of the transmission eigenvalue problem for Maxwell equations

Hoài-Minh Nguyên, Jean Louis-Alexandre Fornerod

Cakoni and Nguyen recently proposed very general conditions on the coefficients of Maxwell equations for which they established the discreten ess of the set of eigenvalues of the transmission problem and studied their locations. In this paper, we establish ...

2021

Waveguide modes spatially resolved by low-loss STEM-EELS

Duncan Thomas Lindsay Alexander

In an era of new developments in nanomaterials analysis enabled by the unprecedented spatial and energy resolutions of electron energy-loss spectroscopy in the scanning transmission electron microscope (STEM-EELS), it remains that the vast majority of work ...

2021

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