Zobrazeno 1 - 10
of 17 398
pro vyhledávání: '"A, Bonato"'
Lazy burning is a recently introduced variation of burning where only one set of vertices is chosen to burn in the first round. In hypergraphs, lazy burning spreads when all but one vertex in a hyperedge is burned. The lazy burning number is the mini
Externí odkaz:
http://arxiv.org/abs/2412.04389
Autor:
Bonato, Matteo, Leisawitz, David, De Zotti, Gianfranco, Sommovigo, Laura, Shivaei, Irene, Urry, C. Megan, Farrah, Duncan, Spencer, Locke, Ricketti, Berke V., Rana, Hannah, Aalto, Susanne, Sanders, David B., Mundy, Lee G.
Far-infrared (FIR) surveys are critical to probing the co-evolution of black holes and galaxies, since of order half the light from accreting black holes and active star formation is emitted in the rest-frame infrared over $0.5\lesssim z \lesssim 10$
Externí odkaz:
http://arxiv.org/abs/2411.01216
Autor:
Salami, Riccardo, Buzzega, Pietro, Mosconi, Matteo, Bonato, Jacopo, Sabetta, Luigi, Calderara, Simone
Model merging has emerged as a crucial technique in Deep Learning, enabling the integration of multiple models into a unified system while preserving performance and scalability. In this respect, the compositional properties of low-rank adaptation te
Externí odkaz:
http://arxiv.org/abs/2410.17961
We present a Bayesian algorithm to identify generators of open quantum system dynamics, described by a Lindblad master equation, that are compatible with measured experimental data. The algorithm, based on a Markov Chain Monte Carlo approach, assumes
Externí odkaz:
http://arxiv.org/abs/2410.17942
The global banking system has faced increasing challenges in combating money laundering, necessitating advanced methods for detecting suspicious transactions. Anti-money laundering (or AML) approaches have often relied on predefined thresholds and ma
Externí odkaz:
http://arxiv.org/abs/2409.00823
Autor:
Bonato, Tommaso, Kabbani, Abdul, Ghalayini, Ahmad, Dohadwala, Mohammad, Papamichael, Michael, De Sensi, Daniele, Hoefler, Torsten
Most datacenter transport protocols traditionally depend on in-order packet delivery, a legacy design choice that prioritizes simplicity. However, technological advancements, such as RDMA, now enable the relaxation of this requirement, allowing for m
Externí odkaz:
http://arxiv.org/abs/2407.21625
We investigate the lazy burning process for Latin squares by studying their associated hypergraphs. In lazy burning, a set of vertices in a hypergraph is initially burned, and that burning spreads to neighboring vertices over time via a specified pro
Externí odkaz:
http://arxiv.org/abs/2407.20370
Autor:
Bonato, Matteo, Baronchelli, Ivano, Casasola, Viviana, De Zotti, Gianfranco, Trobbiani, Leonardo, Ruli, Erlis, Tailor, Vidhi, Bianchi, Simone
We exploit the DustPedia sample of galaxies within approximately 40 Mpc, selecting 388 sources, to investigate the correlations between IR luminosity (L$_{\rm IR}$), the star formation rate (SFR), and the CO(1-0) luminosity (L$_{\rm CO}$) down to muc
Externí odkaz:
http://arxiv.org/abs/2407.10801
Autor:
De Zotti, G., Bonato, M., Giulietti, M., Massardi, M., Negrello, M., Algera, H. S. B., Delhaize, J.
We argue that the difference in infrared-to-radio luminosity ratio between local and high-redshift star-forming galaxies reflects {the alternative physical conditions} -- including magnetic field configurations -- of the dominant population of star-f
Externí odkaz:
http://arxiv.org/abs/2407.04825
Autor:
Mosconi, Matteo, Sorokin, Andriy, Panariello, Aniello, Porrello, Angelo, Bonato, Jacopo, Cotogni, Marco, Sabetta, Luigi, Calderara, Simone, Cucchiara, Rita
The use of skeletal data allows deep learning models to perform action recognition efficiently and effectively. Herein, we believe that exploring this problem within the context of Continual Learning is crucial. While numerous studies focus on skelet
Externí odkaz:
http://arxiv.org/abs/2407.01397