Zobrazeno 1 - 10
of 2 250
pro vyhledávání: '"Salaün, P."'
We introduce a theoretical and practical framework for efficient importance sampling of mini-batch samples for gradient estimation from single and multiple probability distributions. To handle noisy gradients, our framework dynamically evolves the im
Externí odkaz:
http://arxiv.org/abs/2407.15525
We develop a graph neural network (GNN) to compute, within a time budget of 1 to 2 milliseconds required by practical systems, the optimal linear precoder (OLP) maximizing the minimal downlink user data rate for a Cell-Free Massive MIMO system - a ke
Externí odkaz:
http://arxiv.org/abs/2406.04456
Autor:
Chauhan, Vinod Kumar, Clifton, Lei, Salaün, Achille, Lu, Huiqi Yvonne, Branson, Kim, Schwab, Patrick, Nigam, Gaurav, Clifton, David A.
While machine learning algorithms hold promise for personalised medicine, their clinical adoption remains limited. One critical factor contributing to this restraint is sample selection bias (SSB) which refers to the study population being less repre
Externí odkaz:
http://arxiv.org/abs/2405.07841
Autor:
Salaün, Olivier, Piedboeuf, Frédéric, Berre, Guillaume Le, Hermelo, David Alfonso, Langlais, Philippe
Keyphrase generation has primarily been explored within the context of academic research articles, with a particular focus on scientific domains and the English language. In this work, we present EUROPA, a dataset for multilingual keyphrase generatio
Externí odkaz:
http://arxiv.org/abs/2403.00252
Autor:
Huang, Xingchang, Salaün, Corentin, Vasconcelos, Cristina, Theobalt, Christian, Öztireli, Cengiz, Singh, Gurprit
Most of the existing diffusion models use Gaussian noise for training and sampling across all time steps, which may not optimally account for the frequency contents reconstructed by the denoising network. Despite the diverse applications of correlate
Externí odkaz:
http://arxiv.org/abs/2402.04930
Autor:
Abode, Daniel, Adeogun, Ramoni, Salaün, Lou, Abreu, Renato, Jacobsen, Thomas, Berardinelli, Gilberto
In this paper, we present an unsupervised approach for frequency sub-band allocation in wireless networks using graph-based learning. We consider a dense deployment of subnetworks in the factory environment with a limited number of sub-bands which mu
Externí odkaz:
http://arxiv.org/abs/2401.00950
Machine learning problems rely heavily on stochastic gradient descent (SGD) for optimization. The effectiveness of SGD is contingent upon accurately estimating gradients from a mini-batch of data samples. Instead of the commonly used uniform sampling
Externí odkaz:
http://arxiv.org/abs/2311.14468
Autor:
Korać, Miša, Salaün, Corentin, Georgiev, Iliyan, Grittmann, Pascal, Slusallek, Philipp, Myszkowski, Karol, Singh, Gurprit
Independently estimating pixel values in Monte Carlo rendering results in a perceptually sub-optimal white-noise distribution of error in image space. Recent works have shown that perceptual fidelity can be improved significantly by distributing pixe
Externí odkaz:
http://arxiv.org/abs/2310.02955
Autor:
Jacques Dzuko Kamga, Romain Floch, Kevin Kerleguer, David Bourhis, Romain Le Pennec, Simon Hennebicq, Pierre-Yves Salaün, Ronan Abgral
Publikováno v:
Cancer Imaging, Vol 24, Iss 1, Pp 1-8 (2024)
Abstract Introduction The pulmonary Hot Clot artifact (HCa) on 18F-FDG PET/CT is a poorly understood phenomenon, corresponding to the presence of a focal tracer uptake without anatomical lesion on combined CTscan. The hypothesis proposed in the liter
Externí odkaz:
https://doaj.org/article/8c9fba91b298450f9248a840156a673b
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-8 (2024)
Abstract The decision to accept a deceased donor organ offer for transplant, or wait for something potentially better in the future, can be challenging. Clinical decision support tools predicting transplant outcomes are lacking. This project uses int
Externí odkaz:
https://doaj.org/article/1661f210166b4a3eb2027f0a858b3eb3