Zobrazeno 1 - 10
of 6 334
pro vyhledávání: '"P. Reynaud"'
Latent Video Diffusion Models can easily deceive casual observers and domain experts alike thanks to the produced image quality and temporal consistency. Beyond entertainment, this creates opportunities around safe data sharing of fully synthetic dat
Externí odkaz:
http://arxiv.org/abs/2411.04956
The Dzyaloshinskii-Lifshitz-Pitaevskii (DLP) theory of Casimir forces predicts a repulsion between two material surfaces separated by a third medium with an intermediate dielectric function. This DLP repulsion paradigm constitutes an important exampl
Externí odkaz:
http://arxiv.org/abs/2410.18961
Autor:
Garcia, Pablo Soler, Lukovic, Petar, Reynaud, Lucie, Sgobbi, Andrea, Bruni, Federica, Brun, Martin, Zünd, Marc, Bollati, Riccardo, Pollefeys, Marc, Blum, Hermann, Bauer, Zuria
Human-robot interaction through mixed reality (MR) technologies enables novel, intuitive interfaces to control robots in remote operations. Such interfaces facilitate operations in hazardous environments, where human presence is risky, yet human over
Externí odkaz:
http://arxiv.org/abs/2410.11110
Although powerful for image generation, consistent and controllable video is a longstanding problem for diffusion models. Video models require extensive training and computational resources, leading to high costs and large environmental impacts. More
Externí odkaz:
http://arxiv.org/abs/2410.05322
Autor:
Reynaud, Hadrien, Baugh, Matthew, Dombrowski, Mischa, Cechnicka, Sarah, Meng, Qingjie, Kainz, Bernhard
We introduce the Joint Video-Image Diffusion model (JVID), a novel approach to generating high-quality and temporally coherent videos. We achieve this by integrating two diffusion models: a Latent Image Diffusion Model (LIDM) trained on images and a
Externí odkaz:
http://arxiv.org/abs/2409.14149
Autor:
Killian, Carina, Blumer, Philipp, Crivelli, Paolo, Kloppenburg, Daniel, Nez, Francois, Nesvizhevsky, Valery, Reynaud, Serge, Schreiner, Katharina, Simon, Martin, Vasiliev, Sergey, Widmann, Eberhard, Yzombard, Pauline
A low energy particle confined by a horizontal reflective surface and gravity settles in gravitationally bound quantum states. These gravitational quantum states (GQS) were so far only observed with neutrons. However, the existence of GQS is predicte
Externí odkaz:
http://arxiv.org/abs/2407.15443
Autor:
Cechnicka, Sarah, Ball, James, Baugh, Matthew, Reynaud, Hadrien, Simmonds, Naomi, Smith, Andrew P. T., Horsfield, Catherine, Roufosse, Candice, Kainz, Bernhard
Diagnosing medical conditions from histopathology data requires a thorough analysis across the various resolutions of Whole Slide Images (WSI). However, existing generative methods fail to consistently represent the hierarchical structure of WSIs due
Externí odkaz:
http://arxiv.org/abs/2407.13277
Autor:
Reynaud, Hadrien, Meng, Qingjie, Dombrowski, Mischa, Ghosh, Arijit, Day, Thomas, Gomez, Alberto, Leeson, Paul, Kainz, Bernhard
To make medical datasets accessible without sharing sensitive patient information, we introduce a novel end-to-end approach for generative de-identification of dynamic medical imaging data. Until now, generative methods have faced constraints in term
Externí odkaz:
http://arxiv.org/abs/2406.00808
The present work aims at proving mathematically that a neural network inspired by biology can learn a classification task thanks to local transformations only. In this purpose, we propose a spiking neural network named CHANI (Correlation-based Hawkes
Externí odkaz:
http://arxiv.org/abs/2405.18828
We prove oracle inequalities for a penalized log-likelihood criterion that hold even if the data are not independent and not stationary, based on a martingale approach. The assumptions are checked for various contexts: density estimation with indepen
Externí odkaz:
http://arxiv.org/abs/2405.10582