collaborators

5 papers

cond-mat.supr-con2026

Anomalously high quasiparticle thermal conductivity in the underdoped cuprate superconductor HgBaCuO

Jordan Baglo, Quentin Barthélemy, Étienne Lefrançois +4

The single-layer cuprate superconductor HgBaCuO (Hg1201) is an ideal candidate for investigating many properties of cuprates with minimal disorder and without the co…

cs.CV2026

Equivariant Splitting: Self-supervised learning from incomplete data

Victor Sechaud, Jérémy Scanvic, Quentin Barthélemy +2

Self-supervised learning for inverse problems allows to train a reconstruction network from noise and/or incomplete data alone. These methods have the potential of enabling learnin…

cs.CV2026

UNet-AF: An alias-free UNet for image restoration

Jérémy Scanvic, Quentin Barthélemy, Julián Tachella

The simplicity and effectiveness of the UNet architecture makes it ubiquitous in image restoration, image segmentation, and diffusion models. They are often assumed to be equivaria…

cond-mat.supr-con2025

Thermal Hall conductivity in the strongest cuprate superconductor: Estimate of the mean free path in the trilayer cuprate HgBaCaCuO

Munkhtuguldur Altangerel, Quentin Barthélemy, Étienne Lefrançois +12

The thermal Hall conductivity of the trilayer cuprate HgBaCaCuO (Hg1223) - the superconductor with the highest critical temperature at ambient pressure -…

cs.CV2025

Translation-Equivariance of Normalization Layers and Aliasing in Convolutional Neural Networks

Jérémy Scanvic, Quentin Barthélemy, Julián Tachella

The design of convolutional neural architectures that are exactly equivariant to continuous translations is an active field of research. It promises to benefit scientific computing…