Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Tonolini, Francesco"'
Autor:
Shi, Zhengxiang, Tonolini, Francesco, Aletras, Nikolaos, Yilmaz, Emine, Kazai, Gabriella, Jiao, Yunlong
Semi-supervised learning (SSL) is a popular setting aiming to effectively utilize unlabelled data to improve model performance in downstream natural language processing (NLP) tasks. Currently, there are two popular approaches to make use of unlabelle
Externí odkaz:
http://arxiv.org/abs/2305.13002
Forward and Inverse models in HCI:Physical simulation and deep learning for inferring 3D finger pose
Autor:
Murray-Smith, Roderick, Williamson, John H., Ramsay, Andrew, Tonolini, Francesco, Rogers, Simon, Loriette, Antoine
We outline the role of forward and inverse modelling approaches in the design of human--computer interaction systems. Causal, forward models tend to be easier to specify and simulate, but HCI requires solutions of the inverse problem. We infer finger
Externí odkaz:
http://arxiv.org/abs/2109.03366
Publikováno v:
Opt. Express 28, 29486-29495 (2020)
The ability to image through turbid media such as organic tissues, is a highly attractive prospect for biological and medical imaging. This is challenging however, due to the highly scattering properties of tissues which scramble the image informatio
Externí odkaz:
http://arxiv.org/abs/2008.10465
We propose a new probabilistic method for unsupervised recovery of corrupted data. Given a large ensemble of degraded samples, our method recovers accurate posteriors of clean values, allowing the exploration of the manifold of possible reconstructed
Externí odkaz:
http://arxiv.org/abs/2006.16938
Autor:
Turpin, Alex, Musarra, Gabriella, Kapitany, Valentin, Tonolini, Francesco, Lyons, Ashley, Starshynov, Ilya, Villa, Federica, Conca, Enrico, Fioranelli, Francesco, Murray-Smith, Roderick, Faccio, Daniele
Traditional paradigms for imaging rely on the use of a spatial structure, either in the detector (pixels arrays) or in the illumination (patterned light). Removal of the spatial structure in the detector or illumination, i.e., imaging with just a sin
Externí odkaz:
http://arxiv.org/abs/1912.01413
Autor:
Gabbard, Hunter, Messenger, Chris, Heng, Ik Siong, Tonolini, Francesco, Murray-Smith, Roderick
Publikováno v:
Nature Physics 18, 112-117 (2022)
Gravitational wave (GW) detection is now commonplace and as the sensitivity of the global network of GW detectors improves, we will observe $\mathcal{O}(100)$s of transient GW events per year. The current methods used to estimate their source paramet
Externí odkaz:
http://arxiv.org/abs/1909.06296
Machine learning methods for computational imaging require uncertainty estimation to be reliable in real settings. While Bayesian models offer a computationally tractable way of recovering uncertainty, they need large data volumes to be trained, whic
Externí odkaz:
http://arxiv.org/abs/1904.06264
Autor:
Lyons, Ashley, Tonolini, Francesco, Boccolini, Alessandro, Repetti, Audrey, Henderson, Robert, Wiaux, Yves, Faccio, Daniele
Publikováno v:
Nature Photonics; 13; 575-579 (2019)
Imaging through a strongly diffusive medium remains an outstanding challenge in particular in association with applications in biological and medical imaging. Here we propose a method based on a single-photon time-of-flight camera that allows, in com
Externí odkaz:
http://arxiv.org/abs/1808.01135
The ability to know what is hidden around a corner or behind a wall provides a crucial advantage when physically going around the obstacle is impossible or dangerous. Previous solutions to this challenge were constrained e.g. by their physical size,
Externí odkaz:
http://arxiv.org/abs/1503.01699
Accurately establishing the state of large-scale quantum systems is an important tool in quantum information science; however, the large number of unknown parameters hinders the rapid characterisation of such states, and reconstruction procedures can
Externí odkaz:
http://arxiv.org/abs/1407.7426