Zobrazeno 1 - 10
of 8 542
pro vyhledávání: '"Rege, A"'
Nanoporous materials are characterized by their complex porous morphology illustrated by the presence of a solid network and voids. The fraction of these voids is characterized by the porosity of the structure, which influences the bulk mechanical pr
Externí odkaz:
http://arxiv.org/abs/2410.05112
Large Language Models (LLMs) have demonstrated impressive performance across various tasks. However, current training approaches combine standard cross-entropy loss with extensive data, human feedback, or ad hoc methods to enhance performance. These
Externí odkaz:
http://arxiv.org/abs/2409.13641
Autor:
Cambrin, Daniele Rege, Militone, Gabriele Scaffidi, Colomba, Luca, Malnati, Giovanni, Apiletti, Daniele, Garza, Paolo
Designing effective game tutorials is crucial for a smooth learning curve for new players, especially in games with many rules and complex core mechanics. Evaluating the effectiveness of these tutorials usually requires multiple iterations with teste
Externí odkaz:
http://arxiv.org/abs/2408.08396
Autor:
Cambrin, Daniele Rege, Poeta, Eleonora, Pastor, Eliana, Cerquitelli, Tania, Baralis, Elena, Garza, Paolo
Segmentation of crop fields is essential for enhancing agricultural productivity, monitoring crop health, and promoting sustainable practices. Deep learning models adopted for this task must ensure accurate and reliable predictions to avoid economic
Externí odkaz:
http://arxiv.org/abs/2408.07040
Estimating global tree canopy height is crucial for forest conservation and climate change applications. However, capturing high-resolution ground truth canopy height using LiDAR is expensive and not available globally. An efficient alternative is to
Externí odkaz:
http://arxiv.org/abs/2408.04523
Earthquakes are commonly estimated using physical seismic stations, however, due to the installation requirements and costs of these stations, global coverage quickly becomes impractical. An efficient and lower-cost alternative is to develop machine
Externí odkaz:
http://arxiv.org/abs/2407.18128
Large foundation models pretrained on raw web-scale data are not readily deployable without additional step of extensive alignment to human preferences. Such alignment is typically done by collecting large amounts of pairwise comparisons from humans
Externí odkaz:
http://arxiv.org/abs/2406.08469
We build upon recent work on using Machine Learning models to estimate Hamiltonian parameters using continuous weak measurement of qubits as input. We consider two settings for the training of our model: (1) supervised learning where the weak measure
Externí odkaz:
http://arxiv.org/abs/2404.05526
Autor:
Cambrin, Daniele Rege, Garza, Paolo
Earthquake monitoring is necessary to promptly identify the affected areas, the severity of the events, and, finally, to estimate damages and plan the actions needed for the restoration process. The use of seismic stations to monitor the strength and
Externí odkaz:
http://arxiv.org/abs/2403.18116
We derive the two dimensional incompressible Euler equation as a quasineutral limit of the Vlasov-Poisson equation using a modulated energy approach. We propose a strategy which enables to treat solutions where the gradient of the velocity is merely
Externí odkaz:
http://arxiv.org/abs/2403.14080