Zobrazeno 1 - 10
of 34 679
pro vyhledávání: '"Gallø, A."'
We introduce nvTorchCam, an open-source library under the Apache 2.0 license, designed to make deep learning algorithms camera model-independent. nvTorchCam abstracts critical camera operations such as projection and unprojection, allowing developers
Externí odkaz:
http://arxiv.org/abs/2410.12074
Autor:
Fernández, Daniel Gallo, van der Klis, Robert, Matişan, Rǎzvan-Andrei, Partyka, Janusz, Gavves, Efstratios, Papa, Samuele, Lippe, Phillip
While vision transformers are able to solve a wide variety of computer vision tasks, no pre-training method has yet demonstrated the same scaling laws as observed in language models. Autoregressive models show promising results, but are commonly trai
Externí odkaz:
http://arxiv.org/abs/2410.10012
Autor:
Fernández, Daniel Gallo, Matişan, Rǎzvan-Andrei, Muñoz, Alejandro Monroy, Vasilcoiu, Ana-Maria, Partyka, Janusz, Veljković, Tin Hadži, Jazbec, Metod
Diffusion models have achieved unprecedented performance in image generation, yet they suffer from slow inference due to their iterative sampling process. To address this, early-exiting has recently been proposed, where the depth of the denoising net
Externí odkaz:
http://arxiv.org/abs/2410.09633
Autor:
Gallo, Daniela, Liguori, Angelica, Ritacco, Ettore, Caviglione, Luca, Durante, Fabrizio, Manco, Giuseppe
To achieve accurate and unbiased predictions, Machine Learning (ML) models rely on large, heterogeneous, and high-quality datasets. However, this could raise ethical and legal concerns regarding copyright and authorization aspects, especially when in
Externí odkaz:
http://arxiv.org/abs/2410.05819
Autor:
Gallo, Oihane
We analyze the problem of locating a public facility on a line in a society where agents have either single-peaked or single-dipped preferences. We consider the domain analyzed in Alcalde-Unzu et al. (2024), where the type of preference of each agent
Externí odkaz:
http://arxiv.org/abs/2410.03387
Autor:
Milardi, C., Alesini, D., Behtouei, M., Bilanishvili, S., Bini, S., Boscolo, M., Buonomo, B., Cantarella, S., Ciarma, A., De Santis, A., Di Pasquale, E., Di Giulio, C., Di Pirro, G., Foggetta, L., Franzini, G., Gallo, A., Gargana, R., Incremona, S., Liedl, A., Michelotti, A., Piersanti, L., Quartullo, D., Ricci, R., Rotundo, U., Spampinati, S., Stecchi, A., Stella, A., Vannozzi, A., Zobov, M.
The DA{\Phi}NE operations during the last year have been devoted to deliver a statistically significant data sample to perform the first-ever measurement of kaonic deuterium X-ray transitions to the fundamental level. Operations for the SIDDHARTA-2 d
Externí odkaz:
http://arxiv.org/abs/2409.17845
Autor:
Yang, Guitao, Gallo, Alexander J., Barboni, Angelo, Ferrari, Riccardo M. G., Serrani, Andrea, Parisini, Thomas
This paper examines the properties of output-redundant systems, that is, systems possessing a larger number of outputs than inputs, through the lenses of the geometric approach of Wonham et al. We begin by formulating a simple output allocation synth
Externí odkaz:
http://arxiv.org/abs/2409.17705
Supermassive black holes (SMBHs) can grow through both accretion and mergers. It is still unclear how SMBHs evolve under these two channels from high redshifts to the SMBH population we observe in the local universe. Observations can directly constra
Externí odkaz:
http://arxiv.org/abs/2409.16364
This paper compares the accuracy of tail risk forecasts with a focus on including realized skewness and kurtosis in "additive" and "multiplicative" models. Utilizing a panel of 960 US stocks, we conduct diagnostic tests, employ scoring functions, and
Externí odkaz:
http://arxiv.org/abs/2409.13516
Autor:
Moerman, Evgeny, Gallo, Alejandro, Irmler, Andreas, Schäfer, Tobias, Hummel, Felix, Grüneis, Andreas, Scheffler, Matthias
We investigate the convergence of quasi-particle energies for periodic systems to the thermodynamic limit using increasingly large simulation cells corresponding to increasingly dense integration meshes in reciprocal space. The quasi-particle energie
Externí odkaz:
http://arxiv.org/abs/2409.03721